In Deep Web, users usually obtain data information through a unified query interface. Currently, query interfaces generally require pattern matching between attributes. In order to improve the accuracy and recall of m:n pattern matching, this paper proposes a complex pattern matching algorithm based on clustering, CSM, which matches grouped attributes and synonymous attributes as a whole, can effectively find m:n matches, and has a high accuracy rate.
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