Rewarding Term Location Information to Enhance Probabilistic Information Retrieval

被引：0

作者：

Zhao, Jiashu ^{[1
]}

Huang, Jimmy Xiangji ^{[2
]}

Wu, Shicheng ^{[2
]}

机构：

[1] York Univ, Dept Comp Sci & Engn, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON, Canada

[2] York Univ, Sch Informat Technol, Informat Retrieval & Knowledge Management Res Lab, Toronto, ON, Canada

来源：

SIGIR 2012: PROCEEDINGS OF THE 35TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL | 2012年

关键词：

BM25-RT; Influence Shape Function;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：1137 / 1138

页数：2

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