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2003
ACM

Bayesian extension to the language model for ad hoc information retrieval

9 years 3 months ago
Bayesian extension to the language model for ad hoc information retrieval
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. Categories and Subject Descriptors H [3]: 3—Retrieval models General Terms Algorithms, Performance, Theory Keywords Information Retrieval, Ad Hoc Retrieval, Ad Hoc Language Model, Bayesian Language Model
Hugo Zaragoza, Djoerd Hiemstra, Michael E. Tipping
Added 05 Jul 2010
Updated 05 Jul 2010
Type Conference
Year 2003
Where SIGIR
Authors Hugo Zaragoza, Djoerd Hiemstra, Michael E. Tipping
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