关键词: 深层网络, 数据源聚类, 文本聚类, 频繁项集, 数据集成

Abstract: There are thousands of data sources hiding behind the Deep Web pages which can be accessed through structured query interfaces. Organizing these data sources by their domains has become an important step in Deep Web data integration process. Existing methods mainly focus on query interface schema and query results which have the disadvantages of  difficulty in extracting interface schemas and deficiency of submitting queries to the database. A method based on frequent itemsets is proposed to cluster the data sources by their domains. This method considers the Web page text information such as title, key words and label text and solves the problems of overdependency on the query interface and high dimensionality of text processing in traditional solutions. Experimental results show effectiveness and efficiency of this method.

Key words: Deep Web, data source clustering, text clustering, frequent itemsets, data integration