Data Extraction from Deep Web Pages

In this paper, we propose a novel model to extract data from Deep Web pages. The model has four layers, among which the access schedule, extraction layer and data cleaner are based on the rules of structure, logic and application. In the experiment section, we apply the new model to three intelligent system, scientific paper retrieval, electronic ticket ordering and resume searching. The results show that the proposed method is robust and feasible.