›› 2013, Vol. 28 ›› Issue (2): 382-393.doi: 10.1007/s11390-013-1338-0

Special Issue: Artificial Intelligence and Pattern Recognition; Data Management and Data Mining

• Database and Data Management • Previous Articles     Next Articles

Query Intent Disambiguation of Keyword-Based Semantic Entity Search in Dataspaces

Dan Yang1,2 (杨丹), Student Member, CCF, Member, ACM De-Rong Shen1* (申德荣), Senior Member, CCF, Member, ACM, IEEE, Ge Yu1 (于戈), Senior Member, CCF, Member, ACM, IEEE, Yue Kou1 (寇月), Member, CCF, ACM and Tie-Zheng Nie1 (聂铁铮), Member, CCF, ACM   

  1. 1 College of Information Science and Engineering, Northeastern University, Shenyang 110004, China;
    2 Software College, University of Science and Technology LiaoNing, Anshan 114044, China
  • Received:2012-02-16 Revised:2012-09-25 Online:2013-03-05 Published:2013-03-05
  • Supported by:

    This research was supported by the National Basic Research 973 Program of China under Grant No. 2012CB316201, the National Natural Science Foundation of China under Grant Nos. 60973021, 61033007, 61003060, and the Fundamental Research Funds for the Central Universities of China under Grant No. N100704001.

Keyword query has attracted much research attention due to its simplicity and wide applications. The inherent ambiguity of keyword query is prone to unsatisfied query results. Moreover some existing techniques on Web query, keyword query in relational databases and XML databases cannot be completely applied to keyword query in dataspaces. So we propose KeymanticES, a novel keyword-based semantic entity search mechanism in dataspaces which combines both keyword query and semantic query features. And we focus on query intent disambiguation problem and propose a novel three-step approach to resolve it. Extensive experimental results show the effectiveness and correctness of our proposed approach.

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