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

所属专题: Artificial Intelligence and Pattern Recognition Data Management and Data Mining

• Special Section on Selected Paper from NPC 2011 • 上一篇    下一篇


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   

  • 收稿日期:2012-02-16 修回日期:2012-09-25 出版日期:2013-03-05 发布日期:2013-03-05

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.

由于简单性和广泛的应用使得关键字查询吸引了大量的研究关注。关键字查询固有的模糊性容易产生不满意的查询结果。此外, 一些现有的Web查询、关系数据库、XML数据库上的关键字查询技术不能被完全适用于数据空间中的关键字查询。因此我们提出一种新的数据空间中基于关键字的语义实体搜索机制KeymanticES, 它结合了关键字查询和语义查询的特性。我们专注于查询意图消歧问题, 并提出了一种新的三步骤方法来解决这个问题。大量的实验结果表明我们提出方法的有效性和正确性。

Abstract: 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.

[1] Hristidis V, Papakonstantinou Y. Discover: Keyword searchin relational databases. In Proc. the 28th VLDB, Aug., 2002,pp.670-681.

[2] Hristidis V, Gravano L, Papakonstantinou Y. Efficient IR-style keyword search over relational databases. In Proc. the29th VLDB, Sept. 2003, pp.850-861.

[3] Luo Y, Lin X, Wang W et al. Spark: Top-k keyword searchengine on relational databases. In Proc. ICDE, Apr. 2008,pp.1552-1555.

[4] Demidova E, Zhou X, Nejdl W. IQp: Incremental query con-struction, a probabilistic approach. In Proc. the 26th ICDE,Mar. 2010, pp.349-352.

[5] Fan J, Li G L, Zhou L Z. Interactive SQL query suggestion:Making databases user-friendly. In Proc. the 27th ICDE,Apr. 2011, pp.351-362.

[6] Schmidt A, Kersten M L, Windhouwer M. Querying XMLdocuments made easy: Nearest concept queries. In Proc. the17th ICDE, Apr. 2001, pp.321-329.

[7] Xu Y, Papakonstantinou Y. Efficient keyword search forsmallest LCAs in XML databases. In Proc. SIGMOD, June2005, pp.537-538.

[8] Liu Z Y, Walker J, Chen Y. XSeek: A semantic XML searchengine using keywords. In Proc. the 33rd VLDB, Sept. 2007,pp.1330-1333.

[9] Li Y, Yu C, Jagadish H V. Schema-free XQuery. In Proc. the30th VLDB, Aug. 31-Sept. 3, 2004, pp.72-83.

[10] Yang D, Shen D R, Nie T Z et al. Layered graph data modelfor data management of dataspace support platform. In Proc.the 12th WAIM, Sept. 2011, pp.353-365.

[11] Brin S, Page L. The anatomy of a large-scale hypertextualweb search engine. Computer Networks and ISDN Systems,1998, 30(1/7): 107-117.

[12] Derose P, Shen W, Chen F et al. DBLife: A communityinformation management platform for the database researchcommunity. In Proc. CIDR, Jan. 2007, pp.169-172.

[13] Zhai C. Statistical language models for information retrieval:A critical review. Foundations and Trends in InformationRetrieval, 2008, 2(3): 137-213.

[14] Chu E, Baid A, Chai X et al. Combining keyword search andforms for ad hoc querying of databases. In Proc. SIGMOD,June 29-July 2, 2009, pp.349-360.

[15] Tata S, Lohman G M. SQAK: Doing more with keywords. InProc. SIGMOD, June 2008, pp.889-902.

[16] Venkatesh G, Yeye H, Dong X. Keyword++: A frameworkto improve keyword search over entity databases. In Proc.VLDB, Sept. 2010, pp.711-722.

[17] Nikos S, Stelios P, Panayiotis T. Structured annotations ofweb queries. In Proc. SIGMOD, June 2010, pp.771-782.

[18] Paprizos S, Ntoulas A, Shafer J et al. Answering web queriesusing structured data sources. In Proc. SIGMOD, June 29-July 2, 2009, pp.1127-1130.

[19] Cheng T, Lauw H W, Paparizos S. Fuzzy matching of Webqueries to structured data. In Proc. ICDE, Mar. 2010,pp.713-716.

[20] Demidova E, Zhou X, Zenz G et al. SUITS: Faceted user in-terface for constructing structured queries from keywords. InProc. DASFAA, Apr. 2009, pp.772-775.

[21] Pound J, IIyas I F, Weddell G E. Expressive and 癳xibleaccess to web-extracted data: A keyword-based structuredquery language. In Proc. SIGMOD, June 2010, pp.423-434.

[22] Bergamaschi S, Domnori E, Guerra F. Keyword search overrelational databases: A metadata approach. In Proc. SIG-MOD, June 2011, pp.565-576.

[23] Bergamaschi S, Guerra F, Rota S et al. A hidden Markovmodel approach to keyword-based search over relationaldatabases. In Proc. ER, Oct. 31-Nov. 3, 2011, pp.328-331.

[24] Graupmann J, Schenkel R, Weikum G. The sphereSearch en-gine for unified ranked retrieval of heterogeneous XML andweb documents. In Proc. VLDB, Aug. 30-Sept. 2, 2005,pp.529-540.

[25] Bao Z F, Ling T W, Chen B et al. Effective XML key-word search with relevance oriented ranking. In Proc. ICDE,Mar. 29-Apr. 2, 2009, pp.517-528.

[26] Li G L, Ooi B C, Feng J H et al. EASE: An effective 3-in-1keyword search method for unstructured, semi-structured andstructured data. In Proc. SIGMOD, June 2008, pp.903-914.
No related articles found!
Full text



[1] 刘明业; 洪恩宇;. Some Covering Problems and Their Solutions in Automatic Logic Synthesis Systems[J]. , 1986, 1(2): 83 -92 .
[2] 陈世华;. On the Structure of (Weak) Inverses of an (Weakly) Invertible Finite Automaton[J]. , 1986, 1(3): 92 -100 .
[3] 高庆狮; 张祥; 杨树范; 陈树清;. Vector Computer 757[J]. , 1986, 1(3): 1 -14 .
[4] 陈肇雄; 高庆狮;. A Substitution Based Model for the Implementation of PROLOG——The Design and Implementation of LPROLOG[J]. , 1986, 1(4): 17 -26 .
[5] 黄河燕;. A Parallel Implementation Model of HPARLOG[J]. , 1986, 1(4): 27 -38 .
[6] 闵应骅; 韩智德;. A Built-in Test Pattern Generator[J]. , 1986, 1(4): 62 -74 .
[7] 唐同诰; 招兆铿;. Stack Method in Program Semantics[J]. , 1987, 2(1): 51 -63 .
[8] 闵应骅;. Easy Test Generation PLAs[J]. , 1987, 2(1): 72 -80 .
[9] 张钹; 张铃;. Statistical Heuristic Search[J]. , 1987, 2(1): 1 -11 .
[10] 朱鸿;. Some Mathematical Properties of the Functional Programming Language FP[J]. , 1987, 2(3): 202 -216 .
版权所有 © 《计算机科学技术学报》编辑部
本系统由北京玛格泰克科技发展有限公司设计开发 技术支持:support@magtech.com.cn