A Simulated Study of Implicit Feedback Models - White, Ryen W.; Jose, Joemon M.; Rijsbergen, C.J. van; Ruthven, Ian (26th Annual European Conference on Information Retrieval (ECIR 2004), Sunderland, United Kingdom, 2004)
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.
Best Student Paper Award