Bayesian Extension to the Language Model for Ad Hoc Information Retrieval


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 (pp. pp. 4-9).

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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
Additional information:Imported from EWI/DB PMS [db-utwente:inpr:0000003269]
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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