Bayesian Extension to the Language Model for Ad Hoc Information Retrieval


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Zaragoza, H. and Hiemstra, D. and Tipping, M. and Robertson, S.E. (2003) Bayesian Extension to the Language Model for Ad Hoc Information Retrieval. In: Proceedings of the 26th Annual International ACM Conference on Research and Development in Information Retrieval (SIGIR 2003), 28 Jul - 1 Aug 2003, Toronto, Canada.

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Abstract:We propose a Bayesian extension to the ad-hoc Language Model. Many smoothed estimators used for the multinomial query model in ad-hoc Language Models (including Laplace and Bayes-smoothing) are approximations to the Bayesian predictive distribution. In this paper we derive the full predictive distribution in a form amenable to implementation by classical IR models, and then compare it to other currently used estimators. In our experiments the proposed model outperforms Bayes-smoothing, and its combination with linear interpolation smoothing outperforms all other estimators.
Item Type:Conference or Workshop Item
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Electrical Engineering, Mathematics and Computer Science (EEMCS)
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Link to this item:http://purl.utwente.nl/publications/63543
Official URL:http://doi.acm.org/10.1145/860435.860439
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