A Re-ranking Method Based on Cloud Model

摘要：

By introducing cloud model, this paper presents a reranking method which improves the accuracy of the IR (information retrieval) while recall is preserved. It is rare in traditional Chinese information retrieval to consider uncertainty while calculating the related degree of the query and each document in the result set. This paper researches IR in a perspective of uncertainty by introducing cloud model, measures the relevance between the query and document by the uncertainty degree that using document represents the query, and then re-ranks the result set Experiments on NTCIR-5 (the 5th NII Test Collection for IR Systems) document collection for SLIR (Single Language IR) show that this method achieves an 18.08％ and 26.50％ improvement comparing to the initial retrieval method without any re-ranking.

关键词： Information retrieval Re-ranking Cloud model Uncertainty

作者: Maoyuan Zhang Zhenxia Lou Jan Wan Jinguang Chen

作者单位: Department of Computer Science and Technology Central China Normal University Wuhan, China Engineering & Research Center for Information Technology on Education Central China Normal Universit

会议类型: 国际会议

会议名称: 2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 1424-1428

在线出版日期: 2011-12-24（万方平台首次上网日期，不代表论文的发表时间）