Describing the semantic relation of the deep web query interfaces using ontology extended LAV

被引:0
|
作者
Liang H. [1 ,2 ]
Zuo W.-L. [1 ,3 ]
Ren F. [1 ,3 ]
机构
[1] Department of Computer Science and Technology, Jilin University, Jilin Changchun
[2] Department of Information, Changchun Taxation College, Jilin Changchun
[3] Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun
关键词
Deep web; Information fusion; Local as view; Ontology; Query interface; WordNet;
D O I
10.4304/jsw.5.1.89-98
中图分类号
学科分类号
摘要
The key element in a Deep Web information fusion system is the data source modeling problem, which is the determinant technical factor of the whole system. The query interfaces provided by the Deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the lower generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of extracting attributes and semantic relationships from the interfaces utilizing Ontology is present in this paper, and WordNet is introduced as an Ontology instrument. The semantic relationships between semantic related attributes are evaluated by the WordNet. The meaningless attributes are instantiated by instance information embedded in the interfaces. A semantic matrix is generated and used to evaluate the semantic related groups in the specific domains. The expression ability of LAV is extended by the mapping and matching mechanism based on the semantic related groups. The experiment is carried out on the famous dataset, and the results show the efficiency of Ontology extended LAV of building mappings between local schemas and mediator schema. © 2010 ACADEMY PUBLISHER.
引用
收藏
页码:89 / 98
页数:9
相关论文
共 50 条
  • [1] Automatic Integration of Deep Web Query Interfaces based on Ontology
    Wang, Ying
    Peng, Tao
    Zuo, Wanli
    He, Fengling
    ICCIT: 2009 FOURTH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCES AND CONVERGENCE INFORMATION TECHNOLOGY, VOLS 1 AND 2, 2009, : 1654 - 1659
  • [2] Identification and classification of Deep Web query interfaces via ontology
    Qiang B.
    Cai G.
    Wen Y.
    Wu C.
    Tang C.
    International Journal of Advancements in Computing Technology, 2011, 3 (09) : 33 - 40
  • [3] Query Interface Schema Extracting from Deep Web using Ontology
    Sun, Yong
    Wang, Shang
    Li, Zhenyuan
    Liu, Chang
    Peng, Tao
    Qiu, Yuhang
    2021 INTERNATIONAL CONFERENCE ON IMAGE, VIDEO PROCESSING, AND ARTIFICIAL INTELLIGENCE, 2021, 12076
  • [5] Schema Extraction for Deep Web Query Interfaces Using Heuristics Rules
    Chichang Jou
    Information Systems Frontiers, 2019, 21 : 163 - 174
  • [6] Parsing Query Interfaces of Deep Web: from Specialization to Generalization
    Ren Fei
    Liang Hao
    Han Guo-xing
    Zhang Jin-hao
    Bai Yu-na
    2009 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL 3, PROCEEDINGS, 2009, : 252 - +
  • [7] A New Clustering Algorithm for Deep Web Query Interfaces
    Chao, L. V.
    Lin Peiguang
    Nie Peiyao
    ITESS: 2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES, PT 2, 2008, : 661 - 668
  • [8] Research on the Integration of Deep Web Query Interfaces
    Liu, Yongjun
    Xie, Conghua
    Chang, Jinyi
    2014 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C 2014), 2014, : 332 - 335
  • [9] Heuristics-Based Schema Extraction for Deep Web Query Interfaces
    Jou, Chichang
    Cheng, Yucheng
    2017 IEEE 18TH INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION (IEEE IRI 2017), 2017, : 389 - 396
  • [10] Accessing Deep Web Using Automatic Query Translation Technique
    Liang, Hao
    Zuo, Wanli
    Ren, Fei
    Sun, Chong
    FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 2, PROCEEDINGS, 2008, : 267 - 271