| 摘要: |
| 模式匹配是模式集成、数据仓库、电子商务以及语义查询等领域中的一个基础问题,近来已经成为研究的热点,并取得了丰硕的成果.这些成果主要利用元素(典型的为关系模式中的属性)自身的信息来挖掘元素语义,目前,这方面的研究已经相当成熟.结构信息作为模式中一种重要的信息,能够为提高模式匹配的精确性提供有用的支持,但是目前关于如何利用结构信息提高模式匹配的精确性的研究还很少.将模式元素之间的相似度分为语义相似度(根据元素自身信息得到的相似度)和结构相似度(根据元素之间的关联关系得到的相似度),并采用新的统计方法计算元素间的结构相似度,然后再综合考虑语义相似度得到元素间的相似概率;最后根据相似概率得到模式元素间的映射关系(模式元素之间的对应关系).实验结果表明,该算法在查准率、查全率及全面性等方面都优于已有的其他算法. |
| 关键词: 模式匹配 函数依赖 结构匹配 匹配概率 |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.60873030 (国家自然科学基金); the National High-Tech Research and Development Plan of China under Grant No.2007AA01Z309 (国家高技术研究发展计划(863)); the National Defense Pre-Research Foundation of |
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| Structure Matching Method Based on Functional Dependencies |
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LI Guo-Hui,DU Xiao-Kun,HU Fang-Xiao,YANG Bing,TANG Xiang-Hong
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| Abstract: |
| Schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing and semantic query processing. Recently it has become a research hotspot, and most of the achievements are about the use of element’s own information. Research about element’s own information is very mature at present. As an important piece of information in a schema, structure information can be useful information for schema matching, but the research of structure information is far behind that of element’s own information. This paper divides the similarity between two elements into linguistic similarity and structural similarity, and gets the structural similarity by a new statistic method, and then gets the matching probability by integrating the linguistic similarity and structural similarity. At last, the paper gets the mapping between schema elements according to the matching probability. Extensive simulation experiments are conducted and the results show that this algorithm is better than other algorithms in various performance metrics. |
| Key words: schema matching functional dependency structure match matching probability |
