Cluster-based Schema Matching for Deep Web
Li Na · Microcomputer Information · 2009
In Deep Web, users obtain the data information through the uniform query interface in the same domains. Presently, the query interface needs to find attribute correspondences between schemas. However, in order to obtain the effective data from Deep Web, it is necessary to improve the study of the m:n matching. This paper proposes Clustering-based Schema Matching (CSM), a new complex schema matching approach which could effectively discover both simple and complex matching with very high accuracy in time polynomial to the number of attributes and the number of schemas through matching the grouping attribute and synonym.