@workingpaper{

   Author = {Bainbridge, D. and Inglis, S.J.},

   Title = {Musical image compression},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/25},

   Pages = {1-10},

      Year = {1997} }







@workingpaper{

   Author = {Barbour, R.H. and Yeo, A.W.},

   Title = {Internationalising a spreadsheet for Pacific Basin languages},

   Publisher = {Department of Computer Science, University of Waikato},

   Number = {97/17},

      Year = {1997} }







@workingpaper{

   Author = {Cleary, J.G. and Littin, R.H. and McWha, J. and Pearson, M.W.},

   Title = {Constraints on parallelism beyond 10 instructions per cycle},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/27},

   Pages = {1-15},

      Year = {1997} }







@workingpaper{

   Author = {Cockburn, A. and Jones, S.R.},

   Title = {Design issues for World Wide Web navigation visualisation tools},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/2},

      Year = {1997} }







@workingpaper{

   Author = {Cunningham, S.J. and Littin, J.N. and Witten, I.H.},

   Title = {Applications of machine learning in information retrieval},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/6},

      Year = {1997} }







@workingpaper{

   Author = {Frank, E.T. and Wang, Y. and Inglis, S.J. and Holmes, G. and Witten, I.H.},

   Title = {Using model trees for classification},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/12},

      Year = {1997} }







@workingpaper{

   Author = {Holmes, G.},

   Title = {Discovering inter-attribute relationships},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/13},

      Year = {1997} }







@workingpaper{

   Author = {Holmes, G. and Rogers, W.J.},

   Title = {Freezing rich fragments of the World Wide Web},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/11},

      Year = {1997} }







@workingpaper{

   Author = {Holmes, G. and Smith, T.C. and Rogers, W.J.},

   Title = {Computer concepts without computers: a first course in computer science},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/7},

      Year = {1997} }







@workingpaper{

   Author = {Humphrey, M.C.},

   Title = {A graphical notation for the design of information visualisations},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/5},

   Month = {14/5/04},

      Year = {1997} }







@workingpaper{

   Author = {Jones, S.R. and Marsh, S.},

   Title = {A dynamic and flexible representation of social relationships in CSCW},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/1},

      Year = {1997} }







@workingpaper{

   Author = {Jones, S.R. and McInnes, S.},

   Title = {A graphical user interface for Boolean query specification},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/31},

   Pages = {1-18},

      Year = {1997} }







@workingpaper{

   Author = {Littin, R.H. and Cleary, J.G.},

   Title = {Effects of re-ordered memory operations on parallelism},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/28},

   Pages = {1-13},

      Year = {1997} }







@workingpaper{

   Author = {Nevill-Manning, C.G. and Reed, T. and Witten, I.H.},

   Title = {Extracting text from PostScript},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/10},

      Year = {1997} }







@workingpaper{

   Author = {Nevill-Manning, C.G. and Witten, I.H. and Paynter, G.W.},

   Title = {Browsing in digital libraries: a phrase-based approach},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/4},

      Year = {1997} }







@workingpaper{

   Author = {Peeters, R. and Smith, T.C.},

   Title = {Fast convergence with a greedy tag-phrase dictionary},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/23},

   Pages = {1-10},

      Year = {1997} }







@workingpaper{

   Author = {Phillips, C. and McKauge, J.},

   Title = {OZCHI'96 Industry Session: Sixth Australian Conference on Human-Computer Interaction},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/29},

      Year = {1997} }







@workingpaper{

   Author = {Rauterberg, M. and Oestreicher, L. and Grundy, J.C.},

   Title = {Proceedings of the INTERACT97 Combined Workshop on CSCW in HCI-worldwide},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/16},

      Year = {1997} }







@workingpaper{

   Author = {Smith, L.A. and McNab, R.J.},

   Title = {A sight-singing tutor},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/8},

      Year = {1997} }







@workingpaper{

   Author = {Teahan, W.J. and Cleary, J.G.},

   Title = {Adaptive models of English text},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/30},

   Pages = {1-28},

      Year = {1997} }







@workingpaper{

   Author = {Teahan, W.J. and Cleary, J.G.},

   Title = {Tag based models of English text},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/24},

   Pages = {1-10},

      Year = {1997} }







@workingpaper{

   Author = {Teahan, W.J. and Inglis, S.J. and Cleary, J.G. and Holmes, G.},

   Title = {Correcting English text using PPM models},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/26},

   Pages = {1-10},

      Year = {1997} }







@workingpaper{

   Author = {Ting, K.M.},

   Title = {Inducing cost-sensitive trees via instance weighting},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/22},

   Pages = {1-16},

      Year = {1997} }







@workingpaper{

   Author = {Ting, K.M. and Low, B.T. and Witten, I.H.},

   Title = {Learning from batched data: model combination vs data combination},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/14},

      Year = {1997} }







@workingpaper{

   Author = {Ting, K.M. and Witten, I.H.},

   Title = {Stacked generalization: when does it work?},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/3},

      Year = {1997} }







@workingpaper{

   Author = {Ting, K.M. and Witten, I.H.},

   Title = {Stacking bagged and dagged models},

   Publisher = {Department of Computer Science, University of Waikato},

   Number = {97/9},

      Year = {1997} }







@workingpaper{

   Author = {Turner, K.},

   Title = {Information seeking, retrieving, reading and storing behaviour of library users},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/15},

   Pages = {1-28},

      Year = {1997} }







@workingpaper{

   Author = {Yeo, A.W. and Barbour, R.H.},

   Title = {Language use in software},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/20},

      Year = {1997} }







@workingpaper{

   Author = {Yeo, A.W. and Barbour, R.H.},

   Title = {Localising a spreadsheet: an Iban example},

   Publisher = {Department of Computer Science University of Waikato},

   Number = {97/18},

      Year = {1997} }







@workingpaper{

   Author = {Yeo, A.W. and Barbour, R.H.},

   Title = {Strategies of internationalisation and localisation: a postmodernist’s perspective},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/19},

      Year = {1997} }







@workingpaper{

   Author = {Yeo, A.W. and Barbour, R.H. and Apperley, M.D.},

   Title = {Usability testing: a Malaysian study},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {97/21},

   Pages = {1-8},

      Year = {1997} }







@workingpaper{

   Author = {Bainbridge, D. and Cunningham, S.J.},

   Title = {Making oral history accessible over the World Wide Web},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/18},

   Pages = {1-25},

      Year = {1998} }







@workingpaper{

   Author = {Bainbridge, D. and McNab, R.J. and Smith, L.A.},

   Title = {Melody based tune retrieval over the World Wide Web},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/17},

   Pages = {1-9},

      Year = {1998} }







@workingpaper{

   Author = {Cleary, J.G. and Graham, I.D. and Pearson, M.W. and McGregor, A.J.},

   Title = {Measuring ATM traffic: final report for New Zealand Telecom},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/14},

   Pages = {1-15},

      Year = {1998} }







@workingpaper{

   Author = {Cleary, J.G. and Trigg, L.E.},

   Title = {Experiences with a weighted decision tree learner},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/10},

   Pages = {1-15},

      Year = {1998} }







@workingpaper{

   Author = {Frank, E.T. and Trigg, L.E. and Holmes, G. and Witten, I.H.},

   Title = {Naive Bayes for regression},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/15},

   Pages = {1-17},

      Year = {1998} }







@workingpaper{

   Author = {Frank, E.T. and Witten, I.H.},

   Title = {Generating accurate rule sets without global optimization},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/2},

   Pages = {1-15},

      Year = {1998} }







@workingpaper{

   Author = {Grundy, J.C.},

   Title = {Proceedings of CBISE'98 Workshop on component based information systems engineering},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/12},

   Pages = {1-107},

      Year = {1998} }







@workingpaper{

   Author = {Henson, M.C. and Reeves, S.V.},

   Title = {A logic for the schema calculus},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/5},

   Pages = {1-20},

      Year = {1998} }







@workingpaper{

   Author = {Henson, M.C. and Reeves, S.V.},

   Title = {New foundations for Z},

   Publisher = {Computer Science University of Waikato},

   Number = {98/6},

   Pages = {1-20},

      Year = {1998} }







@workingpaper{

   Author = {Henson, M.C. and Reeves, S.V.},

   Title = {Revising Z: semantics and logic},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/4},

   Pages = {1-42},

      Year = {1998} }







@workingpaper{

   Author = {Holmes, G. and Cunningham, S.J. and Dela Rue, B.T. and Bollen, A.F.},

   Title = {Predicting apple bruising using machine learning},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/7},

   Pages = {1-8},

      Year = {1998} }







@workingpaper{

   Author = {Jones, S.R.},

   Title = {Link as you type: using key phrases for automated dynamic link generation},

   Publisher = {Computer Science University of Waikato},

   Number = {98/16},

   Pages = {1-9},

      Year = {1998} }







@workingpaper{

   Author = {Jones, S.R.},

   Title = {VQuery: a graphical user interface for Boolean query specification and dynamic result preview},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/3},

   Pages = {1-9},

      Year = {1998} }







@workingpaper{

   Author = {Jones, S.R. and Cunningham, S.J. and McNab, R.J.},

   Title = {An analysis of usage of a digital library},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/13},

   Pages = {1-12},

      Year = {1998} }







@workingpaper{

   Author = {Ting, K.M. and Zheng, Z.},

   Title = {Boosting trees for cost-sensitive classifications},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/1},

   Pages = {1-14},

      Year = {1998} }







@workingpaper{

   Author = {Trigg, L.E.},

   Title = {An entropy gain measure of numeric prediction performance},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/11},

   Pages = {1-11},

      Year = {1998} }







@workingpaper{

   Author = {Williams, M.},

   Title = {An evaluation of passage-level indexing strategies for a technical report archive},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/8},

   Pages = {1-9},

      Year = {1998} }







@workingpaper{

   Author = {Witten, I.H. and McNab, R.J. and Jones, S.R. and Cunningham, S.J. and Bainbridge, D. and Apperley, M.D.},

   Title = {Managing multiple collections, multiple languages, and multiple media in a distributed digital library},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {98/9},

   Pages = {1-17},

      Year = {1998} }







@workingpaper{

   Author = {Apperley, M.D.},

   Title = {Facilitating multiple copy/paste functions},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/6},

   Pages = {1-8},

      Year = {1999} }







@workingpaper{

   Author = {Apperley, M.D. and Spence, R. and Hodge, S.B. and Chester, M.},

   Title = {Browsing tree structures},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/5},

   Pages = {1-14},

      Year = {1999} }







@workingpaper{

   Author = {Bach, J. and Witten, I.H.},

   Title = {Lexical attraction for text compression},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/1},

   Pages = {1-10},

      Year = {1999} }







@workingpaper{

   Author = {Chang, C. and McGregor, A.J. and Holmes, G.},

   Title = {The LRU*WWW proxy cache document replacement algorithm},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/9},

   Pages = {1-11},

      Year = {1999} }







@workingpaper{

   Author = {Cleary, J.G. and Graham, I.D. and McGregor, A.J. and Pearson, M.W. and Ziedins, I. and Curtis, J.P. and Donnelly, S.F. and Martens, J. and Martin, H.S.},

   Title = {High precision traffic measurement by the WAND research group},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/17},

   Pages = {1-11},

      Year = {1999} }







@workingpaper{

   Author = {Frank, E.T. and Witten, I.H.},

   Title = {Reduced-error pruning with significance tests},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/10},

   Pages = {1-42},

      Year = {1999} }







@workingpaper{

   Author = {Groves, L. and Nickson, R. and Reeve, G.R. and Reeves, S.V. and Utting, B.M.},

   Title = {A survey of software requirements specification practices in the New Zealand software industry},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/8},

   Pages = {1-22},

      Year = {1999} }







@workingpaper{

   Author = {Hall, M.A.},

   Title = {Feature selection for discrete and numeric class machine learning},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/4},

   Pages = {1-16},

      Year = {1999} }







@workingpaper{

   Author = {Holmes, G. and Hall, M.A. and Frank, E.T.},

   Title = {Generating rule sets from model trees},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/2},

   Pages = {1-9},

      Year = {1999} }







@workingpaper{

   Author = {Holmes, G. and Trigg, L.E.},

   Title = {A diagnostic tool for tree based supervised classification learning algorithms},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/3},

   Pages = {1-5},

      URL = {25/6/04},

   Year = {1999} }







@workingpaper{

   Author = {Keegan, T.T. and Cunningham, S.J. and Apperley, M.D.},

   Title = {The Niupepa collection: opening the blinds on a window to the past},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/16},

   Pages = {1-9},

      Year = {1999} }







@workingpaper{

   Author = {Paynter, G.W. and Witten, I.H.},

   Title = {Automating iterative tasks with programming by demonstration: a user evaluation},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/7},

   Pages = {1-9},

      Year = {1999} }







@workingpaper{

   Author = {Teahan, W.J. and Wen, Y.Y. and McNab, R.J. and Witten, I.H.},

   Title = {A compression-based algorithm for Chinese word segmentation},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/13},

   Pages = {1-20},

      Year = {1999} }







@workingpaper{

   Author = {Wang, Y. and Witten, I.H.},

   Title = {Clustering with finite data from semi-parametric mixture distributions},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/14},

   Pages = {1-6},

      Year = {1999} }







@workingpaper{

   Author = {Wang, Y. and Witten, I.H.},

   Title = {Pace regression},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/12},

   Pages = {1-27},

      Year = {1999} }







@workingpaper{

   Author = {Witten, I.H. and Frank, E.T. and Trigg, L.E. and Hall, M.A. and Holmes, G. and Cunningham, S.J.},

   Title = {Weka: practical machine learning tools and techniques with Java implementations},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {99/11},

   Pages = {1-4},

      Year = {1999} }







@workingpaper{

   Author = {Frank, E.T. and Chui, C.K. and Witten, I.H.},

   Title = {Text categorization using compression models},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/2},

   Pages = {1-10},

      Year = {2000} }







@workingpaper{

   Author = {Hall, M.A.},

   Title = {Correlation-based feature selection for discrete and numeric class machine learning},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/8},

   Pages = {1-9},

      Year = {2000} }







@workingpaper{

   Author = {Hall, M.A. and Holmes, G.},

   Title = {Benchmarking attribute selection techniques for data mining},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/10},

   Pages = {1-14},

      Year = {2000} }







@workingpaper{

   Author = {Holmes, G. and Hall, M.A.},

   Title = {A development environment for predictive modelling in foods},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/9},

   Pages = {1-13},

      Year = {2000} }







@workingpaper{

   Author = {Jones, S.R. and Mahoui-Guerni, M.},

   Title = {Hierarchical document clustering using automatically extracted keyphrases},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/13},

   Pages = {1-8},

      Year = {2000} }







@workingpaper{

   Author = {Mahoui, A.},

   Title = {One dimensional non-uniform rational B-splines for animation control},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/7},

   Pages = {1-52},

      Year = {2000} }







@workingpaper{

   Author = {Mahoui-Guerni, M. and Cunningham, S.J.},

   Title = {A comparative transaction log analysis of two computing collections},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/12},

   Pages = {1-6},

      Year = {2000} }







@workingpaper{

   Author = {Reeve, G.R. and Reeves, S.V.},

   Title = {m-charts and Z: extending the translation},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/11},

   Pages = {1-56},

      Year = {2000} }







@workingpaper{

   Author = {Reeve, G.R. and Reeves, S.V.},

   Title = {m-charts and Z: hows, whys and wherefores},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/6},

   Pages = {1-24},

      Year = {2000} }







@workingpaper{

   Author = {Ware, M.F. and Frank, E.T. and Holmes, G. and Hall, M.A. and Witten, I.H.},

   Title = {Interactive machine learning—letting users build classifiers},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/4},

   Pages = {1-7},

      Year = {2000} }







@workingpaper{

   Author = {Witten, I.H. and Paynter, G.W. and Frank, E.T. and Gutwin, C.A. and Nevill-Manning, C.G.},

   Title = {KEA: practical automatic keyphrase extraction},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/5},

   Pages = {1-9},

      Year = {2000} }







@workingpaper{

   Author = {Yeates, S.A. and Bainbridge, D. and Witten, I.H.},

   Title = {Using compression to identify acronyms in text},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {00/1},

   Pages = {1-10},

      Year = {2000} }







@workingpaper{

   Author = {Frank, E.T. and Hall, M.A.},

   Title = {A simple approach to ordinal classification},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/5},

      Year = {2001} }







@workingpaper{

   Author = {Jones, S.R. and Lundy, S. and Paynter, G.W.},

   Title = {Interactive document summarisation},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/1},

   Abstract = {This paper describes the Interactive Document Summariser (IDS).  IDS provides dynamic control over document summary characteristics, such as length and topic focus, so that changes made by the user are instantly reflected in an on-screen summary.  ŒSummary-in-context1 vies allow users to move easily between summaries and their source documents.  IDS adopts the technique of sentence extraction, exploiting keyphrases that are automatically extracted from document text as the primary attribute of a sentence extraction algorithm.  We report an evaluation of IDS summaries, which representative end users of on-line documents identified relevant summary sentences in source documents.  IDS summaries were then compared to the recommendations of the users and we report the efficacy of the summaries based on standard precision and recall measures.  In addition, using established evaluation metrics we found that IDS summaries were better than baseline summaries based on within-document sentence ordering.},

      Year = {2001} }







@workingpaper{

   Author = {Jones, S.R. and Paynter, G.W.},

   Title = {Human evaluation of Kea, an automatic keyphrasing system},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/2},

      Year = {2001} }







@workingpaper{

   Author = {Reeve, G.R. and Reeves, S.V.},

   Title = {Experiences using Z animation tools},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/3},

   Pages = {1-15},

      Year = {2001} }







@workingpaper{

   Author = {Utting, B.M.},

   Title = {Data structures for Z testing tools},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/4},

      Year = {2001} }







@workingpaper{

   Author = {Apperley, M.D. and McLeod, L.C. and Masoodian, M. and Paine, L.B. and Phillips, M. and Rogers, W.J. and Thomson, K.},

   Title = {Use of video shadow for small group interaction awareness on a large interactive display surface},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {07/02},

   Pages = {1-10},

   Abstract = {This paper reports work done as part of the Large Interactive Display Surface (LIDS) project at the University of Waikato.  One application of the LIDS equipment is distributed meeting support.  In this context large display surfaces are used as shared workspaces by people at collaborating sites.  A meeting with start with a shared presentation document, typically and agenda document with summary and detail on agenda items as required.  During the meeting, annotations with be made on the shared document, and new pages will be added with notes and drawings. 



To prevent access collisions and generally mediate use of the shared space, mechanisms to provide awareness of actions of people at other sites are required.  In our system a web camera is used to capture a low-resolution image of the person/people near the board on each side.  Rather than transmit the image directly we computed a shadow/silhouette.  The shadow is displayed behind other screen content.  This provides awareness of position and impending write actions and allows intentional pointing to locations of the screen.  It also has the advantage of being transmitted with low bandwidth, being relatively insensitive to low frame rates, and minimizing visual interference with substantive data being displayed on the screen.},

      Year = {2002} }







@workingpaper{

   Author = {Bouckaert, R.},

   Title = {Accuracy bounds for ensembles under 0-1 loss},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {04/02},

   Pages = {1-19},

   Abstract = {This paper is an attempt to increase the understanding in the behavior of ensembles for discrete variables in a quantitative way.  A set of tight upper and lower bounds for the accuracy of an ensemble is presented for wide classes of ensemble algorithms, including bagging and boosting.  The ensemble accuracy is expressed in terms of the accuracies of the members of the ensemble. 



Since those bounds represent best and worst case behavior only, we study typical behavior as well, and discuss its properties.  A parameterised bound is presented which describes ensemble bahavior as a mixture of dependent base classifier and independent base classifier areas.  Some empirical results are presented to support our conclusions.},

      Year = {2002} }







@workingpaper{

   Author = {Cunningham, S.J.},

   Title = {Toward a theory of music information retrieval queries: system design implications},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {05/02},

   Pages = {1-11},

   Abstract = {Interest in the development of content-based music information retrieval (MIR) systems is growing rapidly.  The MIR research community consists of a multidisciplinary amalgam of librarian, digital librarian, information scientists, computer scientists, musicologists, audio engineers, lawyers and business persons.  This multidisciplinary approach has given rise to significant technological advancements in retrieval algorithms, audio interfaces and data representation schemes.},

      Year = {2002} }







@workingpaper{

   Author = {Frank, E.T. and Holmes, G. and Kirkby, R.B. and Hall, M.A.},

   Title = {Racing committees for large datasets},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {03/02},

   Pages = {1-12},

   Abstract = {This paper proposes a method for generating classifiers from large datasets by building a committee of simple base classifiers using a standard boosting algorithm.  It allows the processing of large datasets even if the underlying base learning algorithm cannot efficiently do so.  The basic idea is to split incoming data into chunks and build a committee based on classifiers build from these individual chunks [3].  Our method extends earlier work in two ways:  (a) the best chunk size is chosen automatically by racing committees corresponding to different chunk sizes, and (b) the committees are pruned adaptively to keep the size of each individual committee as small as possible without negatively affecting accuracy.  This paper shows that choosing an appropriate chunk size automatically is important because the accuracy of the resulting committee can vary significantly with the chunk size.  It also shows that pruning is crucial to make the method practical for large datasets in terms of running time and memory requirements.  Surprisingly, the results demonstrate that pruning can also improve accuracy.},

      Year = {2002} }







@workingpaper{

   Author = {Hall, M.A. and Holmes, G.},

   Title = {Benchmarking attribute selection techniques for discrete class data mining},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {02/02},

   Pages = {1-21},

   Abstract = {Data engineering is generally considered to be a central issue in the development of data mining applications.  The success of many learning schemes, in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes.  The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. 



Attribute selection generally involves a combination of search and attribute utility estimation plus evaluation with respect to specific learning schemes.  This leads to a large number of possible permutation and has led to a situation where very few benchmark studies have been conducted. 



This paper presents a benchmark comparison of several attribute selection methods for supervised classification.  All the methods produce an attribute ranking, a useful devise for isolating the individual merit of an attribute. Attribute selection is achieved by cross-validating the attribute rankings with respect to a classification learner to find the best attributes.  Results are reported for a selection of standard data sets and two diverse learning schemes C4.5 and naïve Bayes.},

      Year = {2002} }







@workingpaper{

   Author = {Holmes, G. and Pfahringer, B. and Frank, E.T. and Kirkby, R.B. and Hall, M.A.},

   Title = {A logistic boosting approach to inducing multiclass alternating decision trees},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/02},

   Pages = {1-11},

   Abstract = {The alternating decision tree (ADTree) is a successful classification technique that combine decision trees with the predictive accuracy of boosting into a ser to interpretable classification rules.  The original formulation of the tree induction algorithm restricted attention to binary classification problems.  This paper empirically evaluates several methods for extending the algorithm to the multiclass case by splitting the problem into several two-class LogitBoost procedure to induce alternating decision trees directly.  Experimental results confirm that this procedure is comparable with methods that are based on the original ADTree formulation in accuracy, while inducing much smaller trees.},

      Year = {2002} }







@workingpaper{

   Author = {Nichols, D.M. and Twidale, M.B.},

   Title = {Usability and open source software},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {10/02},

   Pages = {1-15},

   Abstract = {Open source communities have successfully developed many pieces of software although most computer users only use proprietary applications. The usability of open source software is often regarded as one reason for this limited distribution. In this paper we review the existing evidence of the usability of open source software and discuss how the characteristics of open-source development influence usability. We describe how existing human-computer interaction techniques can be used to leverage distributed networked communities, of developers and users, to address issues of usability.},

      Year = {2002} }







@workingpaper{

   Author = {Thomson, K.},

   Title = {Research laboratory survey},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {09/02},

   Pages = {1-30},

   Abstract = {This report represents the results of a survey conducted by the University of Waikato Usability Laboratory of the research laboratories at the Department of Computer Science, The University of Waikato, Hamilton, New Zealand. The study was conducted on behalf of the Department of Computer Science. 



The goal of the research was to: 



Inform the development of future laboratories; 

Inform the process any of re-development of current laboratories; 

Provide information about the use and acceptance of the laboratories.},

      Year = {2002} }







@workingpaper{

   Author = {Thomson, K. and McLeod, L.C.},

   Title = {The Lids research project appendage to usability study report 1/2002},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {08/02},

   Pages = {1-33},

   Abstract = {This report is a follow on to an earlier report (titled: Usability Study Report (1/2002), dated 1 July 2002) that presented the University of Waikato Usability Laboratory’s (Usability Laboratory) analysis of the Large Interactive Display Screen (LIDS) technologies as developed by the LIDS Research Project.},

      Year = {2002} }







@workingpaper{

   Author = {Thomson, K. and McLeod, L.C.},

   Title = {The Lids research project usability study report 1/2002},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {06/02},

   Pages = {1-160},

   Abstract = {This report represents the University of Waikato Usability Laboratory’s (Usability Laboratory) analysis of the Large Interactive Display Screen (LIDS) technologies as developed by the LIDS Research Group. 



The Usability Laboratory conducted three exploratory-type studies of the LIDS technology over January and February 2002.  The studies each focused on individual elements of the LIDS technology, while at the same time contributing to the general understanding and knowledge of the technology.},

      Year = {2002} }







@workingpaper{

   Author = {Utting, B.M. and Toyn, I. and Sun, J. and Martin, A. and Dong, J. and Daley, N.T. and Currie, D.},

   Title = {ZML:XML support for standard Z},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {11/02},

   Pages = {1-20},

   Abstract = {This paper proposes an XML format for standard Z. We describe several earlier XML proposals for Z, the problems and issues that arose, and the rationales behind our new proposal. The new proposal is based upon a comparison of various existing Z annotated syntaxes, to ensure that the mark-up will be widely usable. This XML format is expected to become a central feature of the CZT (Community Z Tools) initiative.},

      Year = {2002} }







@workingpaper{

   Author = {Utting, B.M. and Wang, S.},

   Title = {Object-orientation in standard Z},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {12/02},

   Pages = {1-20},

   Abstract = {The good news of this paper is that an elegant object-oriented specification style is possible in standard Z. The bad news is that this style is rather different to normal Z specifications, more abstract and axiomatic, which means that it is not so well supported by current Z tools such as animators. It also enforces behavioural subtyping, unlike most object-oriented programming languages. This paper explains the proposed style, with examples, and discusses its advantages and disadvantages.},

      Year = {2002} }







@workingpaper{

   Author = {Frank, E.T. and Hall, M.A.},

   Title = {Visualizing class probability estimators},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {02/03},

   Pages = {1-13},

   Month = {February},

   Abstract = {Inducing classifiers that make accurate predictions on future data is a driving force for research in inductive learning.  However, also of importance to the users is how to gain information from the models produced.  Unfortunately, some of the most powerful inductive learning algorithms generate "black boxes"—that is, the representation of the model makes it virtually impossible to gain any insight into what has been learned.  This paper presents a technique that can help the user understand why a classifier makes the predictions that it does by providing a two-dimensional visualization of its class probability estimates.  It requires the classifier to generate class probabilities but most practical algorithms are able to do so (or can be modified to this end).},

      Year = {2003} }







@workingpaper{

   Author = {Frank, E.T. and Hall, M.A. and Pfahringer, B.},

   Title = {Locally weighted naive Bayes},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {04/03},

   Pages = {1-11},

   Month = {April},

   Abstract = {Despite its simplicity, the naive Bayes classifier has surprised machine learning researchers by exhibiting good performance on a variety of learning problems.  Encouraged by these results, researchers have looked to overcome naive Bayes' primary weakness—attribute independence—and improve the performance of the algorithm.  This paper presents a locally weighted version of naive Bayes that relaxes the independence assumption by learning local models at prediction time.  Experimental results show that locally weighted naive Bayes rarely degrades accuracy compared to standard naive Bayes and, in many cases, improves accuracy dramatically.  The main advantage of this method compared to other techniques for enhancing naive Bayes is its conceptual and computational simplicity.},

      Year = {2003} }







@workingpaper{

   Author = {Frank, E.T. and Paynter, G.W.},

   Title = {Predicting Library of Congress Classifications from Library of Congress Subject Headings},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/03},

   Pages = {1-23},

   Month = {January},

   Abstract = {This paper addresses the problem of automatically assigning a Library of Congress Classification (LCC) to work given its set of Library of Congress Subject Headings (LCSH).  LCC are organized in a tree: the root node of this hierarchy comprises all possible topics, and leaf nodes correspond to the most specialized topic areas defined.  We describe a procedure that, given a resource identified by its LCSH, automatically places that resource in the LCC hierarchy.  The procedure uses machine learning techniques and training data from a large library catalog to learn a classification model mapping from sets of LCSH to nodes in the LCC tree.  We present empirical results for our technique showing its accuracy on an independent collection of 50,000 LCSH/LCC pairs.},

      Year = {2003} }







@workingpaper{

   Author = {Frank, E.T. and Xu, X.},

   Title = {Applying propositional learning algorithms to multi-instance data},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {06/03},

   Pages = {1-12},

   Month = {June},

   Abstract = {Multi-instance learning is commonly tackled using special-purpose algorithms.  Development of these algorithms has started because early experiments with standard propositional learners have failed to produce satisfactory results on multi-instance data—more specifically, the Musk data.  In this paper we present evidence that this is not necessarily the case.  We introduce a simple wrapper for applying standard propositional learners to multi-instance problems and present empirical results for the Musk data that are competitive with genuine multi-instance algorithms.  The key features of our new wrapper technique are: (1) it discards the standard multi-instance assumption that there is some inherent difference between positive and negative bags, and (2) it introduces weights to treat instances from different bags differently.  We show that these two modifications are essential for producing good results on the Musk benchmark datasets.},

      Year = {2003} }







@workingpaper{

   Author = {Holmes, G. and Pfahringer, B. and Kirkby, R.B.},

   Title = {Mining data streams using option trees},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {08/03},

   Pages = {1-11},

   Month = {September},

   Abstract = {The data stream model for data mining places harsh restrictions on a learning algorithm.  A model must be induced following the briefest interrogation of the data, must use only available memory and must update itself over time within these constraints.  Additionally, the model must be able to be used for data mining at any point in time.  This paper describes a data stream classification algorithm using an ensemble of option trees.  The ensemble of trees is induced by boosting and iteratively combined into a single interpretable model.  The algorithm is evaluated using benchmark datasets for accuracy against state-of-the-art algorithms that make use of the entire dataset.},

   Keywords = {classification, option trees, ensemble methods, data streams},

   Year = {2003} }







@workingpaper{

   Author = {Jones, M. and Jain, P. and Buchanan, G. and Marsden, G.},

   Title = {From sit-forward to lean-back: using a mobile device to vary interactive pace},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {03/03},

   Pages = {1-13},

   Month = {March},

   Abstract = {Although online, handheld, mobile computers offer new possibilities in searching and retrieving information on the go, the fast-paced, "sit-forward" style of interaction may not be appropriate for all user search needs.  In this paper, we explore how a handheld computer can be used to enable interactive search experiences that vary in pace from fast and immediate through to reflective and delayed.  We describe a system that asynchronously combines an offline handheld computer and an online desktop Personal Computer, and discuss some results of an initial user evaluation.},

      Year = {2003} }







@workingpaper{

   Author = {Jones, S.R. and Jones, M. and Deo, S.J.},

   Title = {Using keyphrases as search result surrogates on small screen devices},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {07/03},

   Pages = {1-33},

   Month = {September},

   Abstract = {This paper investigates user interpretation of search result displays on small screen devices.  Such devices present interesting design challenges given their limited display capabilities, particularly in relation to screen size.  Our aim is to provide users with succinct yet useful representations of search results that allow rapid and accurate decisions to be made about the utility of result documents, yet minimize user actions (such as scrolling), the use of device resources, and the volume of data to be downloaded.  Our hypothesis is that keyphrases that are automatically extracted from documents can support this aim.  We report on a user study that compared how accurately users categorized result documents on small screens when the document surrogates consisted of either keyphrases only, or document titles.  We found no significant performance differences between the two conditions.  In addition to these encouraging results, keyphrases have the benefit that they can be extracted and presented when no other document metadata can be identified.},

   Keywords = {Small screen device, searching, usability evaluation, keyphrase extraction},

   Year = {2003} }







@workingpaper{

   Author = {Reeves, S.V. and Streader, D.},

   Title = {Comparison of data and process refinement},

   Publisher = {University of Waikato},

   Number = {05/03},

   Pages = {1-10},

   Month = {May},

   Abstract = {When is it reasonable, or possible, to refine a one place buffer into a two place buffer?  In order to answer this question we characterise refinement based on substitution in restricted contexts.  We see that data refinement (specifically in Z) and process refinement give differing answers to the original question, and we compare the precise circumstances which give rise to this difference by translating programs and processes into labelled transition systems, so providing a common basis upon which to make the comparison.  We also look at the closely related area of subtyping of objects.  Along the way we see how all these sorts of computational construct are related as far as refinement is concerned, discover and characterise some (as far as we can tell) new sorts of refinement and, finally, point up some research avenues for the future.},

   Keywords = {Data refinement, process refinement, labelled transition systems, Z, subtyping, theoretical paper},

   Year = {2003} }




@workingpaper{

   Author = {Bittner, S. and Hinze, A.},

   Title = {Design and analysis of an efficient distributed event notification service},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {11/2004},

   Pages = {1-44},

   Month = {December},

   Abstract = {Event Notification Services (ENS) use the publish/subscribe paradigm to continuously inform subscribers about events they are interested in.  Subscribers define their interest in so-called profiles.  The event information is provided by event publishers, filtered by the service against the profiles, and then send to the subscribers.  In real-time systems such as facility management, an efficiency filter component is one of the most important design goals.



In this paper, we present our analysis and evaluation of efficient distributed filtering algorithms.  Firstly, we propose a classification and first-cut analysis of distributed filtering algorithms.  Secondly, based on the classification we describe our analysis of selected algorithms.  Thirdly, we describe our ENS prototype DAS that includes three filtering algorithms.  This prototype is tested with respect to efficiency, network traffic and memory consumption.  In this paper, we discuss the results of our practical analysis in detail.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2004/uow-cs-wp-2004-11.pdf},

   Year = {2004} }







@workingpaper{

   Author = {Bouckaert, R.},

   Title = {Bayesian network classifiers in Weka},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {14/2004},

   Pages = {1-23},

   Month = {September},

   Abstract = {Various Bayesian network classifier learning algorithms are implemented in Weka.  This note provides some user documentation and implementation details.  Summary of the main capabilities:

*  Structure learning of Bayesian networks using various hill climbing (K2, B, etc) and general purpose (simulated annealing, tabu search) algorithms.

*  Local score metrics implemented; Bayes, BDe, MDL, entropy, AIC.

*  Global score metrics implemented; leave one out cv, k-fold cv and cumulative cv.

*  Conditional independence based causal recovery algorithm available.

*  Parameter estimation using direct estimates and Bayesian model averaging.

*  GUI for easy inspection of Bayesian networks.

*  Part of Weka allowing systematic experiments to compare Bayes net performance with general purpose classifiers like C4.5, nearest neighbor, support vector, etc.

*  Source code available under GPL allows for integration in other systems and makes it easy to extend.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2004/uow-cs-wp-2004-14.pdf},

   Year = {2004} }







@workingpaper{

   Author = {Frank, E.T. and Kramer, S.},

   Title = {Ensembles of nested dichotomies for multi-class problems},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {06/2004},

   Pages = {1-16},

   Month = {February},

   Abstract = {Nested dichotomies are a standard statistical technique for tackling certain polytomous classification problems with logistic regression.  They can be represented as binary trees that recursively split a multi-class classification task into a system of dichotomies and provide a statistically sound way of applying two-class learning algorithms to multi-class problems (assuming these algorithms generate class probability estimates).  However, there are usually many candidate trees for a given problem and in the standard approach the choice of a particular tree is based on domain knowledge that may not be available in practice.  An alternative is to treat every system of nested dichotomies as equally likely and to form an ensemble classifier based on this assumption.  We show that this approach produces more accurate classifications than applying C4.5 and logistic regression directly to multi-class problems.  Our results also show that ensembles of nested dichotomies produce more accurate classifiers than pairwise classification if both techniques are used with C4.5, and comparable results for logistic regression.  Compared to error-correcting output codes, they are preferable if logistic regression is used, and comparable in the case of C4.5.  An additional benefit is that they generate class probability estimates.  Consequently they appear to be a good general-purpose method for applying binary classifiers to multi-class problems.},

      Year = {2004} }







@workingpaper{

   Author = {Genet, B. and Hinze, A.},

   Title = {Open issues in Semantic Query Optimization in relational DBMS},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {10/2004},

   Pages = {1-30},

   Month = {August},

   Abstract = {After two decades of research into Semantic Query Optimization (SQO) there is clear agreement as to the efficacy of SQO.  However, although there are some experimental implementations there are still no commercial implementations.  We first present a thorough analysis of research into SQO.  We identify three problems which inhibit the effective use of SQO in Relational Database Management Systems (RDBMS).  We then propose solutions to these problems and describe first steps towards the implementation of an effective semantic query optimizer for relational databases.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2004/uow-cs-wp-2004-10.pdf},

   Year = {2004} }







@workingpaper{

   Author = {Holmes, G. and Kirkby, R.B. and Pfahringer, B.},

   Title = {Mining data streams using option trees (revised edition, 2004)},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {03/2004},

   Pages = {1-13},

   Month = {August},

   Abstract = {The data stream model for data mining places harsh restrictions on a learning algorithm.  A model must be induced following the briefest interrogation of the data, must use only available memory and must update itself over time within these constraints.  Additionally, the model must be able to be used for data mining at any point in time.  This paper describes a data stream classification algorithm using an ensemble of option trees.  The ensemble of trees is induced by boosting and iteratively combined into a single interpretable model.  The algorithm is evaluated using benchmark datasets for accuracy against state-of-the-art algorithms that make use of the entire dataset.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2004/uow-cs-wp-2004-03.pdf},

   Year = {2004} }







@workingpaper{

   Author = {Jones, M. and Marsden, G.},

   Title = {"Please turn ON your mobile phone" - first impressions of text-messaging in lectures},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {07/2004},

   Pages = {1-7},

   Month = {May},

   Abstract = {Previous work by Draper and Brown [3] investigated the use of specialized handsets in increate interactivity in lecture settings. Inspired by their encouraging findings we have been exploring the use of conventional mobile phones and text-messaging to allow students to communicate with the lecturer as the class proceeds.  In our pilot-study, students were able to respond to MCQs and send free-text comments and questions to the lecturer via SMS.  Through observations and interviews with students and lecturers, we gained useful impressions of the value of such an approach.  Students enjoyed the opportunity to be more actively involved but voiced concerns about costs.},

      Year = {2004} }







@workingpaper{

   Author = {Jung, D. and Hinze, A.},

   Title = {Event notification services: analysis and transformation of profile definition languages},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {12/2004},

   Pages = {1-51},

   Abstract = {The integration of event information from diverse event notification sources is, as with meta-searching over heterogeneous search engines, a challenging task. Due to the complexity of profile definition languages, known solutions for heterogeneous searching cannot be applied for event notification. In this technical report, we propose transformation rules for profile rewriting. We transform each profile defined at a meta-service into a profile expressed in the language of each event notification source. Due to unavoidable asymmetry in the semantics of different languages, some superfluous information may be delivered to the meta-service. These notifications are then post-processed to reduce the number of spurious messages. We present a survey and classification of profile definition languages for event notification, which serves as basis for the transformation rules. The proposed rules are implemented in a prototype transformation module for a Meta-Service for event notification.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2004/uow-cs-wp-2004-12.pdf},

   Year = {2004} }







@workingpaper{

   Author = {Keegan, T.T. and Cunningham, S.J. and Don, K.},

   Title = {Language switching in a digital library},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {13/2004},

   Pages = {1-7},

   Month = {August},

   Abstract = {In this paper we investigate the effect of default interface language on usage patterns of the Niupepa digital library (a collection of historic Maori language newspapers), by switching the default interface language between Maori and English in alternate weeks. Transaction analysis of the Niupepa collection logs indicates that changing default language affects the length of user sessions and the number of actions within sessions, and that the English language interface was used most frequently.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2004/uow-cs-wp-2004-13.pdf},

   Year = {2004} }







@workingpaper{

   Author = {Masoodian, M. and McKoy, S. and Rogers, W.J. and Ware, D.},

   Title = {DeepDocument: use of a multi-layered display to provide context awareness in text editing},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {05/2004},

   Pages = {1-13},

   Month = {May},

   Abstract = {The most commonly used view in word processing software shows only the paragraphs of text immediately adjacent to the cursor position.  Generally this is appropriate, for example when composing a single paragraph.  However, when reviewing or working on the layout of a document it is necessary to establish awareness of current text in the context of the document as a whole.  This can be done by scrolling or zooming, but when doing so, focus is easily lost and hard to regain.  Furthermore, in a collaborative editing/review setting it is not only necessary for each user to understand their own context, but also to have an awareness of the contexts of the other participants.  Although systems have been developed that provide awareness in collaborative settings, they usually rely on multiple windows, which use valuable screen real-estate.



We have developed a system called DeepDocument using a two-layered LCD display in which both focussed and document-wide views are presented simultaneously.  The overview is shown on the rear display and the focussed view on the front, maintaining full screen size for each.  The physical separation of the layers takes advantage of human depth perception capabilities to allow users to perceive the views independently without having to redirect their gaze.  DeepDocument has been written as an extension to Microsoft Word™.  It also includes awareness features to track focus positions for both single and multiple users.},

   Keywords = {Multi-layered display, context awareness, collaborative awareness, CSCW, text editing, word processing, Deep Video™, Microsoft Word™},

   Year = {2004} }







@workingpaper{

   Author = {Reeve, G.R. and Reeves, S.V.},

   Title = {The syntax and semantics of m-Charts},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {04/2004},

   Pages = {1-65},

   Month = {February},

   Abstract = {m-Charts is a language for specifying the behaviour of reactive systems.  The language is a simplified variant of the well-known language Statecharts that was introduced by Harel [1].  Development of the m-Charts language is ongoing research undertaken under the auspices of the Formal Methods Laboratory of the Computer Science Department, University of Waikato [5].  This paper gives a comprehensive treatment of the syntax and semantic for m-Charts.},

      Year = {2004} }







@workingpaper{

   Author = {Reeves, S.V. and Streader, D.},

   Title = {Atomic components},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/2004},

   Pages = {1-11},

   Month = {February},

   Abstract = {There has been much interest in components that combine the best of state-based and event-based approaches.  The interface of a component can be thought of as its specification and substituting components with the same interface cannot be observed by any user of the components.  Here we will define the semantics of atomic components where both states and event can be part of the interface.  The resulting semantics is very similar to that of (event only) processes.  But it has two main novelties: one, it does not need recursion or unique fixed points to model nontermination; and two, the behaviour of divergence is modelled by abstraction, i.e. the construction of the observational semantics.},

   Keywords = {State and action, components, refinement labelled transition systems, Z},

   Year = {2004} }







@workingpaper{

   Author = {Reeves, S.V. and Streader, D.},

   Title = {Unifying state and process determinism},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {02/2004},

   Pages = {1-10},

   Month = {February},

   Abstract = {If a coin is given to a deterministic robot that interacts with a deterministic vending machine then is the drink that the robot is delivered determined?  Using process definitions of determinism from CSP, CCS or ACP the answer is "no", whereas state-based definitions of determinism can reasonably be construed as giving the answer "yes".



In order to unify what we see as discrepancies in state- and action-based notions of determinism we will consider process algebras over two sets of actions: the active or casual actions of the robot and the passive or reactive actions of the vending machine.  In addition we will add priority to the actions and when two t actions are possible then the t action with the highest priority will be executed.},

   Keywords = {Process algebra, determinism, abstraction, hiding state},

   Year = {2004} }







@workingpaper{

   Author = {Sánchez, J.A. and Twidale, M.B. and Nichols, D.M. and Silva, N.N.},

   Title = {Analyzing library collections with starfield visualizations},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {09/2004},

   Pages = {1-12},

   Month = {July},

   Abstract = {This paper presents a qualitative and formative study of the uses of a starfield-based visualization interface for analysis of library collections.  The evaluation process has produced feedback that suggests ways to significantly improve starfield interfaces and the interaction process to improve their learnability and usability.  The study also gave us clear indication of additional potential uses of starfield visualizations that can be exploited by further functionality and interface development.  We report on resulting implications for the design and use of starfield visualizations that will impact their graphical interface features, their use for managing data quality and their potential for various forms of visual data mining.  Although the current implementation and analysis focuses on the collection of a physical library, the most important contributions of our work will be in digital libraries, in which volume, complexity and dynamism of collections are increasing dramatically and tools are needed for visualization and analysis.},

   Keywords = {Collections, starfields, large information spaces, libraries},

   URL = {http://www.cs.waikato.ac.nz/pubs/wp/2004/uow-cs-wp-2004-09.pdf},

   Year = {2004} }







@workingpaper{

   Author = {Twidale, M.B. and Nichols, D.M.},

   Title = {Usability discussions in open source development},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {08/2004},

   Pages = {1-11},

   Month = {June},

   Abstract = {The public nature of discussion in open source projects provides a valuable resource for understanding the mechanisms of open source software development.  In this paper we explore how open source projects address issues of usability.  We examine bug reports of several projects to characterise how developers address and resolve issues concerning user interfaces and interaction design.  We discuss how bug reporting and discussion systems can be improved to better support bug reporters and open source developers.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2004/uow-cs-wp-2004-08.pdf},

   Year = {2004} }







@workingpaper{

   Author = {Bittner, S. and Hinze, A.},

   Title = {Investigating the memory requirements for publish/subscribe filtering algorithms},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {03/2005},

   Month = {August},

   Abstract = {Various filtering algorithms for publish/subscribe systems have been proposed. One distinguishing characteristic is their internal representation of Boolean subscriptions: They either require conversions into disjunctive normal forms (canonical approaches) or are directly exploited in event filtering (non-canonical approaches).



In this paper we present a detailed analysis and comparison of the memory requirements of canonical and non-canonical filtering algorithms. This includes a theoretical analysis of space usages as well as a verification of our theoretical results by an evaluation of a practical implementation. This practical analysis also considers time (filter) efficiency, which is the other important quality measure of filtering algorithms. By correlating the results of space and time efficiency, we conclude when to use non-canonical and canonical approaches.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2005/uow-cs-wp-2005-03.pdf},

   Year = {2005} }







@workingpaper{

   Author = {Buchanan, G. and Hinze, A.},

   Title = {A distributed directory service for Greenstone},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/2005},

   Pages = {1-18},

   Month = {April},

   Abstract = {Greenstone is a software for creating and maintaining distributed digtal library collections. It provides a sophisticated federation mechanism for the collections. In order to support alerting notification about changes in the distributed collections, we propose a distributed directory service for the management of the distributed Greenstone installations. The Greenstone directory service (GDS) acts on top of the distributed Greenstone structure for the management of collections. this paper describes both, the initial distributed Greenstone structure and the distributed directory service.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2004/uow-cs-wp-2004-01.pdf},

   Year = {2005} }







@workingpaper{

   Author = {Hinze, A. and Malik, P. and Malik, R.},

   Title = {Towards a TIP 3.0 service-oriented architecture: interaction design},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {08/2005},

   Pages = {1-26},

   Month = {September},

   Abstract = {This paper describes our experience when applying formal methods in the design

of the tourist information system TIP, which presents context-sensitive information to mobile users with small screen devices. The dynamics of this system are very complex and pose several challenges, firstly because of the sophisticated interaction of several applications on a small screen device and the user, and secondly because of the need for communication with highly asynchronous event-based information systems. UML sequence diagrams have been used to capture the requirements and possible interactions of the system. In a second step, a formal model has been created using discrete event systems, in order to thoroughly understand and analyse the dynamics of the system. By verifying general properties of the formal model, several conceptual difficulties have been revealed in very early stages of the design process, considerably speeding up the development. This work shows the limitations of typical methods for interaction design when applied to mobile systems using small screen devices and proposes an alternative approach using discrete event systems.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2005/uow-cs-wp-2005-08.pdf},

   Year = {2005} }







@workingpaper{

   Author = {Junmanee, S. and Hinze, A.},

   Title = {Advanced recommendation in a mobile tourist information system},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {04/2005},

   Month = {August},

   Abstract = {An advanced tourist information provider system delivers information regarding sights and events on their users' travel route.  In order to give sophisticated personalized information about tourist attractions to their users, the system is required to consider base data which are user preferences defined in their user profiles, user context, sights context, user travel history as well as their feedback given to the sights they have visited.  In addition to sights information, recommendation  on sights to the user could also be provided.  This project concentrates on combinations of knowledge on recommendation systems and base information given by the users to build a recommendation component in the Tourist Information Provider or TIP system.  To accomplish our goal, we not only examine several tourist information systems but also conduct the investigation on recommendation systems.  We propose a number of approaches for advanced recommendation models in a tourist information system and select a subset of these for implementation to prove the concept.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2005/uow-cs-wp-2005-04.pdf},

   Year = {2005} }







@workingpaper{

   Author = {Kozuka, T. and Hinze, A.},

   Title = {Design and implementation of a filter engine for semantic web documents},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {05/2005},

   Month = {August},

   Abstract = {This report describes our project that addresses the challenge of changes in the semantic web.  Some studies have already been done for the so-called adaptive semantic web, such as applying inferring rules.  In this study, we apply the technology of Event Notification System (ENS).  Treating changes as events, we developed a notification system for such events.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2005/uow-cs-wp-2005-05.pdf},

   Year = {2005} }







@workingpaper{

   Author = {Michel, Y.-R. and Hinze, A.},

   Title = {ApproXFILTER – an approximative XML filter},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {06/2005},

   Pages = {1-16},

   Month = {October},

   Abstract = {Publish/subscribe systems filter published documents and inform their subscribers about documents matching their interests. Recent systems have focussed on documents or messages sent in XML format. Subscribers have to be familiar with the underlying XML format to create meaningful subscriptions. A service might support several providers with slightly differing formats, e.g., several publishers of books. This makes the definition of a successful subscription almost impossible. We propose the use of an approximative language for subscriptions. We introduce the design our ApproXFILTER algorithm for approximative filtering in a pub/sub system. We present the results of our analysis of a prototypical implementation.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2005/uow-cs-wp-2005-06.pdf},

   Year = {2005} }







@workingpaper{

   Author = {Reeves, S.V. and Streader, D.},

   Title = {Constructing programs or processes},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {09/2005},

   Pages = {1-13},

   Month = {December},

   Abstract = {We define interacting sequential programs, motivated originally by constructivist

considerations. We use them to investigate notions of implementation and determinism. Process algebras do not define what can be implemented and what cannot. As we demonstrate it is problematic to do so on the set of all processes. Guided by constructivist notions we have constructed interacting sequential programs which we claim can be readily implemented and are a subset of processes.},

   Keywords = {Process algebra, determinism, cause, refinement, constructive},

   URL = {http://www.cs.waikato.ac.nz/pubs/wp/2005/uow-cs-wp-2005-09.pdf},

   Year = {2005} }







@workingpaper{

   Author = {Reeves, S.V. and Streader, D.},

   Title = {Stepwise refinement of processes},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {07/2005},

   Pages = {1-15},

   Month = {December},

   Abstract = {Industry is looking to create a market in reliable "plug-and-play" components. To model components in a modular style it would be useful to combine event-based and state-based reasoning. One of the first steps in building an event-based model is to decide upon a set of atomic actions. This choice will depend on the formalism used, and may restrict in quite unexpected ways what we are able to formalise. In this paper we illustrate some limits to developing real world processes using existing formalisms, and we define a new notion of refinement, vertical refinement, which addresses some of these limitations. We show that using vertical refinement we can rewrite a specification into a different formalism, allowing us to move between handshake processes, broadcast processes and abstract data types.},

   Keywords = {Components, process, vertical refinement},

   URL = {http://www.cs.waikato.ac.nz/pubs/wp/2005/uow-cs-wp-2005-07.pdf},

   Year = {2005} }







@workingpaper{

   Author = {Witten, I.H. and Bainbridge, D. and Tansley, R. and Huang, C.-Y. and Don, K.},

   Title = {A bridge between Greenstone and DSpace},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {02/2005},

   Pages = {1-10},

   Month = {April},

   Abstract = {Greenstone and Dspace are widely-used software systems for digital libraries, and prospective users sometimes wonder which one to adopt. In fact, the aims of the two are very different, although their domains of application do overlap. This paper describes the systems  and identifies their similarities and differences. We also present StoneD,  a stone bridge between the production versions of Greenstone  and DSpace that allows users of either system to easily migrate to the other, or continue with a combination of both. This bridge eliminates the risk of finding oneself locked in to an inappropriate choice of system. We also discuss other possible opportunities for combining the advantages of the two, to the benefit of the user common of both systems.},

      Year = {2005} }







@workingpaper{

   Author = {Bittner, S. and Hinze, A.},

   Title = {Event distributions in online book auctions},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {03/2006},

   Pages = {1-23},

   Month = {February},

   Abstract = {Current quantitative evaluations in various research areas for pub-lish/subscribe systems use artiﬁcially created event messages to model the system workload. The assumptions made to create these workloads are rather strong and hardly ever described in detail. This does not allow for a repetition of experiments or comparative evaluations of different approaches by different researches.



In this paper, we present an evaluation of the distributions of the values of attributes typically used in online auction scenarios. In particular, we focus on auctions of ﬁction books. We further show our approach of creating event messages by the help of the gained information. Publishing this information on how to create a typical workload for online auctions should allow for the repetition of experiments and the comparison of different evaluations.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2006/uow-cs-wp-2006-03.pdf},

   Year = {2006} }







@workingpaper{

   Author = {Bittner, S. and Hinze, A.},

   Title = {Subscription tree pruning: a structure-independent routing optimization for general-purpose publish/subscribe systems},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {01/2006},

   Pages = {1-31},

   Month = {January},

   Abstract = {A main challenge in distributed publish/subscribe systems is the efficient and scalable routing of incoming information (event messages). For large-scale publish/subscribe services, subscription forwarding has been established as a prevalent routing scheme. It reduces the network traffic for event routing due to selectively forwarding event messages to relevant parts of the network only. To further improve event routing, publish/subscribe systems apply routing optimizations. So far, optimizations for general-purpose publish/subscribe systems are still missing.



In this paper, we present the architecture, realization, and evaluation of our prototype of a large-scale publish/subscribe service applying a novel routing optimization, subscription tree pruning. We also show a comparison of five existing routing optimizations in respect to six important characteristic parameters affecting the suitability of these approaches in practice (including space usage, time efficiency (throughput), and network load). This comparative analysis clearly demonstrates the advantages of subscription pruning over other routing optimizations. In our practical experiments, we then investigate the behavior of our prototype regarding all quantitatively measurable parameters from our previously theoretically analyzed ones. Our evaluation of subscription pruning in this paper is more extensive than previous analyses of any routing optimizations for publish/subscribe systems, which focus on selected parameters only.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2006/uow-cs-wp-2006-01.pdf},

   Year = {2006} }







@workingpaper{

   Author = {Hinze, A. and Jung, D. and Cunningham, S.J.},

   Title = {Proceedings of the Second Computing Women Congress (CWC 2006): Student Papers, Hamilton, New Zealand, 11-19 February 2006},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {02/2006},

   Pages = {1-32},

   Month = {February},

   Abstract = {The Second Computing Women Congress was held at the University of Waikato, Hamilton, New Zealand from February 11th to 19th, 2006.  The Computing Women Congress (CWC) is a Summer University of women in computer science.  It is a meeting-place for female students, academics and professionals who study or work in Information Technology.  CWC provides a forum to learn about and share the latest ideas of computing related topics in a supportive environment.  CWC provides an open, explorative learning and teaching environment.  Experimentation with new styles of learning is encouraged, with an emphasis on hands-on experience and engaging participatory techniques.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2006/uow-cs-wp-2006-02.pdf},

   Year = {2006} }







@workingpaper{

   Author = {Utting, M. and Pretschner, A. and Legeard, B.},

   Title = {A taxonomy of model-based testing},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {04/2006},

      Year = {2006} }
      




@workingpaper{

   Author = {Bittner, S. and Hinze, A.},

   Title = {Arbitrary Boolean advertisements: the final step in supporting the Boolean publish/subscribe model},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {06/2006},

   Pages = {1-46},

   Month = {June},

   Abstract = {Publish/subscribe systems allow for an efficient filtering of incoming information. This filtering is based on the specifications of subscriber interests, which are registered with the system as subscriptions. Publishers conversely specify advertisements, describing the messages they will send later-on. What is missing so far is the support of arbitrary Boolean advertisements in publish/subscribe systems. Introducing the opportunity to specify these richer Boolean advertisements increases the accuracy of publishers to state their future messages compared to currently supported conjunctive advertisements. Thus, the amount of subscriptions forwarded in the network is reduced. Additionally, the system can more time efficiently decide whether a subscription needs to be forwarded and more space efficiently store and index advertisements. 



In this paper, we introduce a publish/subscribe system that supports arbitrary Boolean advertisements and, symmetrically, arbitrary Boolean subscriptions. We show the advantages of supporting arbitrary Boolean advertisements and present an algorithm to calculate the practically required overlapping relationship among subscriptions and advertisements. Additionally, we develop the first optimization approach for arbitrary Boolean advertisements, advertisement pruning. Advertisement pruning is tailored to optimize advertisements, which is a strong contrast to current optimizations for conjunctive advertisements. These recent proposals mainly apply subscription-based optimization ideas, which is leading to the same disadvantages. 



In the second part of this paper, our evaluation of practical experiments, we analyze the efficiency properties of our approach to determine the overlapping relationship. We also compare conjunctive solutions for the overlapping problem to our calculation algorithm to show its benefits. Finally, we present a detailed evaluation of the optimization potential of advertisement pruning. This includes the analysis of the effects of additionally optimizing subscriptions on the advertisement pruning optimization.

},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2006/uow-cs-wp-2006-06.pdf},

   Year = {2006} }







@workingpaper{

   Author = {Hall, M.},

   Title = {A decision tree-based attribute weighting filter for Naive Bayes},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {05/2006},

   Pages = {1-12},

   Month = {May},

   Abstract = {The naive Bayes classiﬁer continues to be a popular learning algorithm for data mining applications due to its simplicity and linear run-time. Many enhancements to the basic algorithm have been proposed to help mitigate its primary weakness—the assumption that attributes are independent given the class. All of them improve the performance of naive Bayes at the expense (to a greater or lesser degree) of execution time and/or simplicity of the ﬁna lmodel. In this paper we present a simple ﬁlter method for setting attribute weights for use with naive Bayes. Experimental results show that naive Bayes with attribute weights rarely degrades the quality of the model compared to standard naive Bayes and, in many cases, improves it dramatically. The main advantages of this method compared to other approaches for improving naive Bayes is its run-time complexity and the fact that it maintains the simplicity of the ﬁnal model.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2006/uow-cs-wp-2006-05.pdf},

   Year = {2006} }







@workingpaper{

   Author = {Reeves, S. and Streader, D.},

   Title = {Liberalising Event B without changing it},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {07/2006},

   Pages = {1-13},

   Month = {July},

   Abstract = {We transfer a process algebraic notion of refinement to the B method by using the well-known bridge between the relational semantics underlying the B machines and the labelled transition system semantics of processes. Thus we define delta refinement on Event B systems. We then apply this new refinement to a problem from the literature that previously could only be solved by retrenchment.},

   Keywords = {process refinement, automatic verification, frame refinement, Event B},

   URL = {http://www.cs.waikato.ac.nz/pubs/wp/2006/uow-cs-wp-2006-07.pdf},

   Year = {2006} }







@workingpaper{

   Author = {Reeves, S. and Streader, D.},

   Title = {LSB - Live and Safe B alternative semantics for Event B},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {08/2006},

   Pages = {1-18},

   Month = {July},

   Abstract = {We define two lifted, total relation semantics for Event B machines: Safe B for

safety-only properties and Live B for liveness properties. The usual Event B proof

obligations, Safe, are sufficient to establish Safe B refinement. Satisfying Safe

plus a simple additional proof obligation ACT_REF is sufficient to establish Live

B refinement. The use of lifted, total relations both prevents the ambiguity of the

unlifted relational semantics and prevents operations being clairvoyant.},

   Keywords = {Process refinement, Event B, Live B, Safe B, LSB},

   URL = {http://www.cs.waikato.ac.nz/pubs/wp/2006/uow-cs-wp-2006-08.pdf},

   Year = {2006} }







@workingpaper{

   Author = {Reeves, S. and Streader, D.},

   Title = {State- and Event-based refinement},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {09/2006},

   Pages = {1-8},

   Month = {September},

   Abstract = {In this paper we give simple example abstract data types, with atomic operations, that are related by data refinement under a definition used widely in the literature, but these abstract data types are not related by singleton failure refinement. This contradicts results found in the literature. Further we show that a common way to change a model of atomic operations to one of value passing operations actually changes the underlying atomic operational semantics.},

   Keywords = {Data refinement, process refinement, singleton failures},

   URL = {http://www.cs.waikato.ac.nz/pubs/wp/2006/uow-cs-wp-2006-09.pdf},

   Year = {2006} }







@workingpaper{

   Author = {Twidale, M.B. and Nichols, D.M.},

   Title = {Computational sense: the role of technology in the education of digital librarians},

   Publisher = {Department of Computer Science, The University of Waikato},

   Number = {10/2006},

   Pages = {1-8},

   Month = {October},

   Abstract = {The rapid progress of digital library technology from research to implementation has created a force for change in the curricula of library schools. The education of future librarians has always had to adapt to new technologies but the pace, complexity and implications of digital libraries pose considerable challenges. In this article we explore how we might successfully blend elements of computer science and library science to produce effective educational experiences for the digital librarians of tomorrow. We first outline the background to current digital librarian education and then propose the concept of computational sense as an appropriate meeting point for these two disciplines.},

      URL = {http://www.cs.waikato.ac.nz/pubs/wp/2006/uow-cs-wp-2006-10.pdf},

   Year = {2006} }









