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Deep Web集成中数据模式映射失效检测方法研究 被引量：2

Research on Detecting Broken Mappings for Deep Web Integration
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摘要 查询接口集成是Deep Web数据集成的关键,在动态环境下,Web数据源的变化会引起数据模式映射的失效,使得查询接口集成维护难度增加,因此数据模式映射失效检测是Deep Web数据集成研究中的热点问题.针对目前数据模式映射失效检测方法的局限,在模糊聚集算子的研究基础上,提出一种适用于数据模式映射失效检测的结果融合算法.通过实验对比测试,并对映射失效检测方法的性能和效率进行了分析和实验,结果证明了提出的方法对于失效模型的检测是有效的. The deep Web integration system employs a set of semantic mappings between the mediated schema and the schemas of Web data sources. In this dynamic environment, sources often undergo changes that invalidate the mappings. Such continuous monitoring is extremely labor intensive, and poses a key bottleneck to the widespread deployment of Web data integration systems in practice. The paper describes DBMFR (Detecting Broken Mappings Based on Fuzzy Reasoning) an automatic solution to detecting broken mappings. Fuzzy aggregation operators are leveraged to calculate the score, which implies whether the mapping is broken. The paper provides a new fuzzy reasoning algorithm based on fuzzy aggregation operators. Experiments over real-world sources demonstrate the effectiveness of our fuzzy-based approach over existing solutions, as well as the utility of our improvements.
作者 缪嘉嘉 李爱平 贾焰 吴泉源
机构地区 国防科学技术大学计算机学院
出处 《计算机研究与发展》 EI CSCD 北大核心 2008年第z1期222-227,共6页 Journal of Computer Research and Development
基金 国家"八六三"高技术研究发展计划基金项目(2004AA112020 2005AA112030) 国家"九七三"重点基础研究发展规划基金项目(2005CB321804)
关键词 DEEP WEB集成 模式映射 模糊聚集算子 Deep Web mapping maintenance fuzzy aggregation operators
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献15

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二级参考文献2

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共引文献3

同被引文献28

  • 1Khare R, An Y, Song Ⅱ-Yeol. Understanding Deep Web search interfaces: A survey [J]. ACM SIGMOD Record, 2010, 39(1): 33-40.
  • 2He Bin, Chang Kevin Chen-Chuan. A holistic paradigm for large scale schema matching [J]. ACM SIGMOD Record, 2004, 33(4): 20-25.
  • 3He Bin, Chang Kevin Chen-Chuan. Automatic complex schema matching across Web query interfaces: A correlation mining approach [J]. ACM Trans on Database Systems, 2006, 31(1): 346-395.
  • 4He Bin, Chang Kevin Chen-Chuan, Han Jiawei. Discovering complex matchings across Web query interfaces: a correlation mining approach [C]//Proc of ACM SIGMOD Int Conf on Knowledge Discovery and Data Mining(KDD). New York: ACM, 2004: 148-157.
  • 5Liu Jie, Wang Nianbin, Liu Fujiang, et al. Complex synonymous matchings based on correlation mining [C] // Proc of the Interoperability for Enterprise Software and Applications China ( IESA ). Washington, DC: IEEE Computer Society, 2009: 175-179.
  • 6He Zhongtian, Hong Jun, Bell David A. Schema matching across query interfaces on the Deep Web [G] //LNCS 5071: Proc of the 25th British National Conf on Databases (BNCOD). Berlin: Springer, 2008:51-62.
  • 7He Zhongtian, Hong Jun, Bell David A. A prioritized collective selection strategy for schema matching across query interfaces [G] //LNCS 3588: Proc of the 26th British National Conf on Databases (BNCOD). Berlin: Springer, 2009:21-32.
  • 8Liu Tantan, Wang Fan, Agrawal G. Instance discovery and schema matching with applications to biological Deep Web data integration [C] //Proc of the IEEE Int Conf on Bioinformatics and Bioengineering(BIBE). Washington, DC IEEE Computer Society, 2010: 304-305.
  • 9Fu Yuchen, Liu Quan, Xu Yunlong, et al. Correlated clustering frame a holistic method of Deep Web schema matching based on data mining[C] //Proc of WRI World Congress on Computer Science and Information Engineering. Washington, DC: IEEE Computer Society, 2009:528-533.
  • 10Wang Rui, Wang Nianbin. Ontology-based Deep Web data interface schemas integration method [C] //Proe of 2nd Int Conf on e-Business and Information System Security (EBISS). Washington, DC: IEEE Computer Society, 2010: 1-4.

引证文献2

二级引证文献4

计算机研究与发展
2008年 第z1期

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