基于词向量的字符串属性语义模式匹配及其求值

K. Nozaki, T. Hochin, Hiroki Nomiya
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引用次数: 8

摘要

基于实例的模式匹配是通过比较实例来确定异构数据库之间的对应关系。异构数据库由大量包含各种属性的表组成,导致数据异构。在这种情况下,考虑语义信息是有效的。本文提出了一种考虑属性语义的基于实例的模式匹配方法。我们使用Word2Vec来匹配字符串的属性。结果表明,可以检测具有高语义相似度的属性之间的匹配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semantic Schema Matching for String Attribute with Word Vectors and its Evaluation
Instance-based schema matching is to determine the correspondences between heterogeneous databases by comparing instances. Heterogeneous databases consist of an enormous number of tables containing various attributes, causing the data heterogeneity. In such cases, it is effective to consider semantic information. In this paper, we propose the instance-based schema matching considering attributes’ semantics. We used Word2Vec to match attributes of character strings. The result shows a possibility to detect matching between attributes with high semantic similarity.
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