EFFECTIVE ENTITY RESOLUTION IN PRODUCT REVIEW DOMAIN

摘要：

This paper is concerned with the problem of entity resolution in the product review domain.Specifically, given many references to product features, we would like to classify references related to one feature into a group.The product feature resolution is important to product review study, such as review ranking.To solve the problem, we propose an approach which combines two types of similarity characteristics:edit distance and context similarity. Experimental results indicate that the proposed approach resolves product features effectively and improves the performance of review ranking significantly.

关键词： Entity resolution Product feature Edit distance Context similarity Review ranking

作者: JING-JING LIU YUN-BO CAO YA-LOU HUANG

作者单位: Intelligent Information Processing Lab, Nankai University, Tianjin, China Microsoft Research Asia, Beijing, China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 106-111

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）