White, R.W. and Jose, J.M. and van Rijsbergen, C.J. and Ruthven, I. (2004) A simulated study of implicit feedback models. In: Advances in Information Retrieval. Lecture Notes in Computer Science, 2997 . Springer-Verlag, Berlin-Heidelberg, pp. 311-326. ISBN 3540213821
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  outperform the other models under investigation.
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