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AAAI
1996

Machine Learning of User Profiles: Representational Issues

8 years 3 months ago
Machine Learning of User Profiles: Representational Issues
As more information becomes available electronically, tools for finding information of interest to users becomes increasingly important. The goal of the research described here is to build a system for generating comprehensible user profiles that accurately capture user interest with minimum user interaction. The research described here focuses on the importance of a suitable generalization hierarchy and representation for learning profiles which are predictively accurate and comprehensible. In our experiments we evaluated both traditional features based on weighted term vectors as well as subject features corresponding to categories which could be drawn from a thesaurus. Our experiments, conducted in the context of a content-based profiling system for on-line newspapers on the World Wide Web (the IDD News Browser), demonstrate the importance of a generalization hierarchy and the promise of combining natural language processing techniques with machine learning (ML) to address an infor...
Eric Bloedorn, Inderjeet Mani, T. Richard MacMilla
Added 02 Nov 2010
Updated 02 Nov 2010
Type Conference
Year 1996
Where AAAI
Authors Eric Bloedorn, Inderjeet Mani, T. Richard MacMillan
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