Exploration of a heuristic approach to threshold learning in adaptive filtering

Chengxiang Zhai, Peter Jansen, David A. Evans

Research output: Contribution to journalConference articlepeer-review

Abstract

In this paper we examine the learning behavior of a heuristic threshold setting approach to information filtering. In particular, we study how different initial threshold settings and different updating parameter settings affect threshold learning. The results on one of the TREC news databases indicate that (1) learning allows recovery from the inevitable non-optimality of the initial conditions, and (2) a greater `willingness to learn' (expressed by a deliberate lowering of the score threshold in the learning stage) does eventually lead to a higher performance in spite of the expected initial performance penalty.

Original languageEnglish (US)
Pages (from-to)360-362
Number of pages3
JournalSIGIR Forum (ACM Special Interest Group on Information Retrieval)
StatePublished - Dec 11 2000
Externally publishedYes
EventProceedings of the 23rd International ACM SIGIR Conference on Research and Development in Infornation Retrieval (SIGIR 2000) - Athens, Greece
Duration: Jul 24 2000Jul 28 2000

ASJC Scopus subject areas

  • Management Information Systems
  • Hardware and Architecture

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