Exploring Topic-based Language Models for Effective Web Information Retrieval


Li, Rongmei and Kaptein, Rianne and Hiemstra, Djoerd and Kamps, Jaap (2008) Exploring Topic-based Language Models for Effective Web Information Retrieval. In: Dutch-Belgian Information Retrieval Workshop, DIR 2008, 14-15 April 2008, Maastricht, the Netherlands (pp. pp. 65-71).

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Abstract:The main obstacle for providing focused search is the relative opaqueness of search request -- searchers tend to express their complex information needs in only a couple of keywords. Our overall aim is to find out if, and how, topic-based language models can lead to more effective web information retrieval. In this paper we explore retrieval performance of a topic-based model that combines topical models with other language models based on cross-entropy. We first define our topical categories and train our topical models on the .GOV2 corpus by building parsimonious language models. We then test the topic-based model on TREC8 small Web data collection for ad-hoc search.Our experimental results show that the topic-based model outperforms the standard language model and parsimonious model.
Item Type:Conference or Workshop Item
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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