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.

Preview

PDF
167Kb

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
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Databases (DB)
Link to this item:	http://purl.utwente.nl/publications/64722
Export this item as:	BibTeX EndNote HTML Citation Reference Manager

Show download statistics for this publication

Repository Staff Only: item control page

Metis ID: 250952