A simulated study of implicit feedback models

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White, R.W. and Jose, J.M. and van Rijsbergen, C.J. and Ruthven, I.; MacDonald, S. and Tait, J., eds. (2004) A simulated study of implicit feedback models. In: Advances in Information Retrieval. Lecture Notes in Computer Science, 2997 . Springer-Verlag, Sunderland, UK, pp. 311-326. ISBN 3540213821 (http://www.cis.strath.ac.uk/research/publications/...)

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Abstract

In this paper we report on a study of implicit feedback models for unobtrusively tracking the information needs of searchers. Such models use relevance information gathered from searcher interaction and can be a potential substitute for explicit relevance feedback. We introduce a variety of implicit feedback models designed to enhance an Information Retrieval (IR) system's representation of searchers' information needs. To benchmark their performance we use a simulation-centric evaluation methodology that measures how well each model learns relevance and improves search effectiveness. The results show that a heuristic-based binary voting model and one based on Jeffrey's rule of conditioning [5] outperform the other models under investigation.

ORCID iDs

White, R.W., Jose, J.M., van Rijsbergen, C.J. and Ruthven, I. ORCID logoORCID: https://orcid.org/0000-0001-6669-5376; MacDonald, S. and Tait, J.
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