A simulated study of implicit feedback models Export

@misc{citeulike:1981540, 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 outperform the other models under investigation.}, author = {White, R. and Jose, J. and van Rijsbergen, C. and Ruthven, I.}, citeulike-article-id = {1981540}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.1029}, citeulike-linkout-1 = {http://citeseer.ist.psu.edu/white04simulated.html}, keywords = {algorithm, evaluation, model, relevance\_feedback}, posted-at = {2008-02-18 12:19:07}, priority = {2}, title = {A simulated study of implicit feedback models}, url = {http://citeseer.ist.psu.edu/white04simulated.html}, year = {2004} }

TY - GEN ID - citeulike:1981540 L3 - citeulike-article-id:1981540 N2 - 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. TI - A simulated study of implicit feedback models KW - algorithm KW - evaluation KW - model KW - relevance_feedback AU - White, R AU - Jose, J AU - van Rijsbergen, C AU - Ruthven, I PY - 2004/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.1029 ER -