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Topic based language models for ad hoc information retrieval

Azzopardi, L; Girolami, M; van Rijsbergen, CJ; (2004) Topic based language models for ad hoc information retrieval. Presented at: IEEE International Joint Conference on Neural Networks (IJCNN), Budapest, HUNGARY.

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Abstract

We propose a topic based approach to language modelling for ad-hoc Information Retrieval (IR). Many smoothed estimators used for the multinomial query model in IR rely upon the estimated background collection probabilities. In this paper, we propose a topic based language modelling approach, that uses a more informative prior based on the topical content of a document. In our experiments, the proposed model provides comparable IR performance to the standard models, but when combined in a two stage language model, it outperforms all other estimated models.

Type: Conference item (UNSPECIFIED)
Title: Topic based language models for ad hoc information retrieval
Event: IEEE International Joint Conference on Neural Networks (IJCNN)
Location: Budapest, HUNGARY
Dates: 25 July 2004 - 29 July 2004
ISBN: 0-7803-8359-1
UCL classification: UCL > School of BEAMS > Faculty of Maths and Physical Sciences
UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Statistical Science
URI: http://discovery.ucl.ac.uk/id/eprint/1339674
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