Tech Reports
Tech Report kmi-03-04 Abstract
A Comparative Study of Term Weighting Methods for Information Filtering
Techreport ID: kmi-03-04
Date: 2003
Author(s): Nikolaos Nanas, Victoria Uren, Anne De Roeck
The users of an information filtering system can only be expected to provide a small amount of information to initialize their user profile. Therefore, term weighting methods for information filtering have somewhat different requirements to those for information retrieval and text categorization. We present a comparative evaluation of term weighting methods, including one novel method, relative document frequency, designed specifically for information filtering. The best weighting methods appear to be those which balance exploiting user input and data from the collection.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Social Software is...
Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.
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