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  • An Analysis of Case-Base Editing in a Spam Filtering System 

    Delany, Sarah Jane; Cunningham, Padraig (Trinity College Dublin, Department of Computer Science, 2004-08)
    Because of the volume of spam email and its evolving nature, any deployed Machine Learning-based spam filtering system will need to have procedures for case-base maintenance. Key to this will be procedures to edit ...
  • The Application of Case-Based Reasoning to Early Software Project Cost Estimation and Risk Assessment 

    Delany, Sarah Jane; Cunningham, Padraig (Trinity College Dublin, Department of Computer Science, 2000-02)
    In this paper we assess the applicability of case-based reasoning to the difficult problem of early software project cost estimation. We conclude that a comprehensive case representation is not available early in the ...
  • An Assessment of Case-Based Reasoning for Spam Filtering 

    Delany, Sarah Jane; Cunningham, Padraig; Coyle, Lorcan (Trinity College Dublin, Department of Computer Science, 2004-11)
    Because of the changing nature of spam, a spam filtering system that uses machine learning will need to be dynamic. This suggests that a case-based (memory-based) approach may work well. Case-Based Reasoning (CBR) is a ...
  • Blame-Based Noise Reduction: An Alternative Perspective on Noise Reduction for Lazy Learning 

    Pasquier, Francois-Xavier; Delany, Sarah Jane; Cunningham, Padraig (Trinity College Dublin, Department of Computer Science, 2005-02-22)
    In this paper we present a new perspective on noise reduction for nearest-neighbour classifiers. Classic noise reduction algorithms such as Repeated Edited Nearest Neighbour remove cases from the training set if they are ...
  • A Case-Based Technique for Tracking Concept Drift in Spam Filtering 

    Delany, Sarah Jane; Cunningham, Padraig; Tsymbal, Alexey; Coyle, Lorcan (Trinity College Dublin, Department of Computer Science, 2004-08-17)
    Clearly, machine learning techiques can play an important role in filtering spam email because ample training data is available to build a robust classifier. However, spam filtering is a particularly challenging task as ...
  • A Comparison of Ensemble and Case-Base Maintenance Techniques for Handling Concept Drift in Spam Filtering 

    Delany, Sarah Jane; Cunningham, Padraig; Tsymbal, Alexey (Trinity College Dublin, Department of Computer Science, 2005)
    The problem of concept drift has recently received considerable attention in machine learning research. One important practical problem where concept drift needs to be addressed is spam filtering. The literature on ...
  • ECUE: A Spam Filter that Uses Machine Learning to Track Concept Drift 

    Delany, Sarah Jane; Cunningham, Padraig (Trinity College Dublin, Department of Computer Science, 2006-02-10)
    While text classification has been identified for some time as a promising application area for Artificial Intelligence, so far few deployed applications have been described. In this paper we present a spam filtering ...
  • Generating Estimates of Classification Confidence for a Case-Based Spam Filter 

    Delany, Sarah Jane; Cunningham, Padraig; Doyle, Donal (Trinity College Dublin, Department of Computer Science, 2005-02-05)
    Producing estimates of classification confidence is surprisingly difficult. One might expect that classifiers that can produce numeric classification scores (e.g. k-Nearest Neighbour or Naive Bayes) could readily produce ...
  • The Limits of CBR in Software Project Estimation 

    Delany, Sarah Jane; Cunningham, Padraig (Trinity College Dublin, Department of Computer Science, 1999-03)
    Software project cost estimation is difficult because of problems of quantifying project size and because of the continual emergence of new technology. This presents as a classic example of a weak theory domain where ...