Statistical Language Models for Information Retrieval A Critical Review
Foundations and Trends in Information Retrieval
Adaptive relevance feedback in information retrieval
Proceedings of the 18th ACM conference on Information and knowledge management
Improvements that don't add up: ad-hoc retrieval results since 1998
Proceedings of the 18th ACM conference on Information and knowledge management
Modeling term proximity for probabilistic information retrieval models
Information Sciences: an International Journal
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Many information retrieval (IR) techniques have been proposed to improve the performance, and some combinations of these techniques has been demonstrated to be effective. However, how to effectively combine them is largely unexplored. It is possible that a method reduces the positive influence of the other one even if both of them are effective separately. In this paper, we propose a new hybrid model which can simply and flexibly combine components of three different IR techniques under a uniform framework. Extensive experiments on the TREC standard collections indicate that our proposed model can outperform the best TREC systems consistently in the ad-hoc retrieval. It shows that the combination strategy in our proposed model is very effective. Meanwhile, this method is also re-useable for other researchers to test whether their new methods are additive to the current technologies.