期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2016
卷号：13
期号：5
出版社：IJCSI Press
摘要：Information integration is an interesting research topic that has recently attracted the attention of researchers. Schema matching is One of the critical issues in the implementation of the plan integrate information. A large number of information sources available on the web, but their contents can be accessed through the query interfaces. As an important step to integrate data sources, we focus on the integration of query interfaces. Holistic schema matching are implemented to deal with the challenges of large-scale schemas. More specifically in the article focus on the integration of semantic mapping fields with the holistic schema matching. In this paper, clustering-based method for matching query interfaces are provided. This method is based on two general observations. First, because of the use of the dictionary is easier to find features that are semantically related to the same query interfaces. Secondly, related features identified in the interfaces can help to find related features in other interfaces. The proposed method, divided into 3 main steps, the first step of pre-processing dataset and automatic manufacturing of dictionary, second step is Completion of first dictionary by user, and the third step, uploading datasets and secondary dictionary and applying proposed algorithms on them. K-Means clustering algorithm was used to apply the proposed method. Algorithm K-Means is very useful for the matching of large-scale. And the results, shows the impact of the proposed methodology and the accuracy and performance of the proposed method. The method has a high accuracy in the range of returns. This method handles simple and complex matching.
关键词：Information integration; query interfaces; holistic schema matching; clustering; web interface
