@inbook{255ccdddcd6945ecac30859b6d19a415,
title = "A simulated study of implicit feedback models",
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.",
keywords = "implicit feedback, computer science, information retrieval, web search, relevance ranking",
author = "R.W. White and J.M. Jose and {van Rijsbergen}, C.J. and I. Ruthven and S. MacDonald and J. Tait",
note = "Paper presented at the 26th European Conference on Information Retrieval (ECIR), 5-7 Apr 2004, Sunderland, UK.; 26th European Conference on Information Retrieval (ECIR) ; Conference date: 05-04-2004 Through 07-04-2004",
year = "2004",
language = "English",
isbn = "3540213821",
volume = "2997",
series = "Lecture Notes in Computer Science",
publisher = "Springer-Verlag",
pages = "311--326",
booktitle = "Advances in Information Retrieval",
}