The TREC-8 Filtering Track Final Report.

Abstract

The TREC-8 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 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 the evaluation results in graphical format, and provides a general commentary on lessons learned from this year's track. 1 Introduction A text filtering system sifts through a stream of arriving information to find documents relevant to a set of user profiles. Unlike the traditional search query, user profiles are persistent, and tend to reflect a long term information need. With user feedback, the system can learn a better pro...