• Predicting Library of Congress Classifications from Library of Congress Subject Headings

    Frank, Eibe; Paynter, Gordon W. (University of Waikato, 2003-01)
    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 ...
  • Visualizing class probability estimators

    Frank, Eibe; Hall, Mark A. (University of Waikato, Department of Computer Science, 2003-02-19)
    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. ...
  • From sit-forward to lean-back: Using a mobile device to vary interactive pace

    Jones, Mark; Jain, Preeti; Buchanan, George; Marsden, Gary (University of Waikato, Department of Computer Science, 2003-03)
    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. ...
  • Locally weighted naive Bayes

    Frank, Eibe; Hall, Mark A.; Pfahringer, Bernhard (University of Waikato, Department of Computer Science, 2003-04)
    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 ...
  • Comparison of data and process refinement

    Reeves, Steve; Streader, David (University of Waikato, Department of Computer Science, 2003-05)
    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 ...
  • Applying propositional learning algorithms to multi-instance data

    Frank, Eibe; Xu, Xin (University of Waikato, Department of Computer Science, 2003-06)
    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 ...
  • Using keyphrases as search result surrogates on small screen devices

    Jones, Steve; Jones, Matt; Deo, Shaleen (University of Waikato, Department of Computer Science, 2003-09)
    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 ...
  • Mining data streams using option trees

    Holmes, Geoffrey; Pfahringer, Bernhard; Kirkby, Richard Brendon (University of Waikato, Department of Computer Science, 2003-09)
    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 ...

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