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The TREC-2001 Filtering Track Report

Published

Author(s)

S E. Robertson, Ian Soboroff

Abstract

The TREC-10 filtering track measures the ability of systems to build persistent user profiles which successfully separate relevant and non-relevant documents. It consists of three major subtasks: adaptive filtering, batch filtering, and routing. In adaptive filtering, the system begins with only a topic statement and a small number of positive examples, and must learn a better profile from on- line feedback. Batch filtering and routing are more traditional machine learning tasks where the system begins with a large sample of evaluated training documents. This report describes the track, presents some evaluation results, and provides a general commentary on lessons learned from this year¿s track.
Citation
OTHER -

Citation

Robertson, S. and Soboroff, I. (2002), The TREC-2001 Filtering Track Report, OTHER, National Institute of Standards and Technology, Gaithersburg, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=51047 (Accessed June 21, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created March 31, 2002, Updated October 12, 2021