Rewarding term location information to enhance probabilistic information retrieval

Authors:
Jiashu Zhao;Jimmy Xiangji Huang;Shicheng Wu
Affiliations:
York University, Toronto, ON, Canada;York University, Toronto, ON, Canada;York University, Toronto, ON, Canada
Venue:
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Year:
2012

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Abstract

We investigate the effect of rewarding terms according to their locations in documents for probabilistic information retrieval. The intuition behind our approach is that a large amount of authors would summarize their ideas in some particular parts of documents. In this paper, we focus on the beginning part of documents. Several shape functions are defined to simulate the influence of term location information. We propose a Reward Term Retrieval model that combines the reward terms' information with BM25 to enhance probabilistic information retrieval performance.