An effective method supporting data extraction and schema recognition on deep web

Abstract

With the rapid development of Internet, data sources on deep web store a large number of high-quality structured data, which demands the development of structured data extraction method. But the existing methods focus on data rather than structure, and some of them are difficult to maintain. To resolve these problems, a complete and effective method supporting data extraction and schema recognition is proposed in this paper. To extract data, a novel algorithm based on clustering is adopted, which is also effective when faced complex data and excessive noise. And a simple extraction rule model is defined to resolve the problem of maintenance. In addition, it does deep mining on result schema recognition. At last, experiments show satisfactory results. © 2008 Springer-Verlag Berlin Heidelberg.