RACE: Finding and Ranking Compact Connected Trees for Keyword Proximity Search over XML Documents

摘要：

In this paper, we study the problem of keyword proximity search over XML documents and leverage the efficiency and effectiveness. We take the disjunctive semantics among input keywords into consideration and identify meaningful compact connected trees as the answers of keyword proximity queries. We introduce the notions of Compact Lowest Common Ancestor (CLCA) and Maximal CLCA (MCLCA) and propose Compact Connected Trees (CCTrees) and Maximal CCTrees (MCCTrees) to efficiently and effectively answer keyword queries. We propose a novel ranking mechanism, RACE, to Rank compAct Connected trEes, by taking into consideration both the structural similarity and the textual similarity. Our extensive experimental study shows that our method achieves both high search effciency and effectiveness, and outperforms existing approaches significantly.

关键词： Lowest Common Ancestor (LCA) Compact LCA (CLCA) Maximal CLCA(MCLCA)

作者: Guoliang Li Jianhua Feng Jianyong Wang Bei Yu Yukai He

作者单位: Department of Computer Science and Technology Tsinghua University, Beijing, China School of Computing National University of Singapore, Singapore

会议类型: 国际会议

会议名称: 第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-04-21（万方平台首次上网日期，不代表论文的发表时间）