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SIGIR
2002
ACM

Novelty and redundancy detection in adaptive filtering

8 years 11 months ago
Novelty and redundancy detection in adaptive filtering
This paper addresses the problem of extending an adaptive information filtering system to make decisions about the novelty and redundancy of relevant documents. It argues that relevance and redundance should each be modelled explicitly and separately. A set of five redundancy measures are proposed and evaluated in experiments with and without redundancy thresholds. The experimental results demonstrate that the cosine similarity metric and a redundancy measure based on a mixture of language models are both effective for identifying redundant documents.
Yi Zhang 0001, James P. Callan, Thomas P. Minka
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where SIGIR
Authors Yi Zhang 0001, James P. Callan, Thomas P. Minka
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