Topic based language models for ad hoc information retrieval

Azzopardi, L. and Girolami, M. and van Rijsbergen, C.J.; (2005) Topic based language models for ad hoc information retrieval. In: 2004 IEEE International Joint Conference on Neural Networks. IEEE, HUN, pp. 3281-3286. ISBN 0780383591

[thumbnail of Azzopardi-etal-IEEE-IJCNN-2004-Topic-based-language-models-for-ad-hoc-information-retrieval]
Text (Azzopardi-etal-IEEE-IJCNN-2004-Topic-based-language-models-for-ad-hoc-information-retrieval)
Accepted Author Manuscript

Download (95kB)| Preview


    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.