DSSM: A Data Sources Selection Model for Deep Web

The deep Web data integration has become more and more important due to the large amount of deep Web data sources. Nevertheless, how to select the most relevant data sources on deep web is still a challenging issue. However, the existing strategies only focus on the data sources interfaces, which are not enough to select the best-effort data sources in the same domain. To solve this problem, an integrative data sources selection model named as DSSM is proposed in this paper, in which, the interface schema, the search mode, the contents in background databases, as well as the quality of data sources are considered together. So the model has the ability to select the best-effort data sources satisfying user queries. After carrying out a series of experiments on real-world sources, we demonstrate the effectiveness of the DSSM model.