Picture of Open Access badges

Discover Open Access research at Strathprints

It's International Open Access Week, 24-30 October 2016. This year's theme is "Open in Action" and is all about taking meaningful steps towards opening up research and scholarship. The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs. Explore recent world leading Open Access research content by University of Strathclyde researchers and see how Strathclyde researchers are committing to putting "Open in Action".


Image: h_pampel, CC-BY

Evaluating implicit feedback models using searcher simulations

White, R.W. and Ruthven, I. and Jose, J.M. and van Rijsbergen, C.J. (2005) Evaluating implicit feedback models using searcher simulations. ACM Transactions on Information Systems, 23 (3). pp. 325-361.

Full text not available in this repository. (Request a copy from the Strathclyde author)


In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simulations. Since these algorithms select additional terms for query modification based on inferences made from searcher interaction, not on relevance information searchers explicitly provide (as in traditional RF), we refer to them as implicit feedback models. We introduce six different models that base their decisions on the interactions of searchers and use different approaches to rank query modification terms. The aim of this article is to determine which of these models should be used to assist searchers in the systems we develop. To evaluate these models we used searcher simulations that afforded us more control over the experimental conditions than experiments with human subjects and allowed complex interaction to be modeled without the need for costly human experimentation. The simulation-based evaluation methodology measures how well the models learn the distribution of terms across relevant documents (i.e., learn what information is relevant) and how well they improve search effectiveness (i.e., create effective search queries). Our findings show that an implicit feedback model based on Jeffrey's rule of conditioning outperformed other models under investigation.