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 language | English (US) |
|---|---|
| Pages (from-to) | 360-362 |
| Number of pages | 3 |
| Journal | SIGIR Forum (ACM Special Interest Group on Information Retrieval) |
| State | Published - 2000 |
| Externally published | Yes |
| Event | Proceedings of the 23rd International ACM SIGIR Conference on Research and Development in Infornation Retrieval (SIGIR 2000) - Athens, Greece Duration: Jul 24 2000 → Jul 28 2000 |
ASJC Scopus subject areas
- Management Information Systems
- Hardware and Architecture