The Study On Deep Web Interface Integration Of Books Area

According to the depth of information on the Web, it can be divided into Deep Web and Surface Web. Since the quality and quantity of information in Deep Web is higher and bigger than that in Surface Web, in order to effectively use these information, it is necessary to establish Deep Web data integration system. Interface integration is an important task for integrating Deep Web resources. This paper mainly studies the query interface integration in Deep Web data integration.The method of interface integration in English area is difficult to effectively applied into the Chinese area; and the method in Chinese area also has some shortages, including: the integrated attributes are not sufficient, the accuracy rate of matching is low and etc. This paper carried out deep research on the interface integration method in view of the above problems. According to the structure of Deep Web interfaces, query interfaces are categorized into four categories in this paper, and we given the formalized expression for these interfaces. Based on above work, this paper presents a Deep Web interface integration approach based on keyword matching, ontology matching and semantic similarity computing. The keyword matching is performed firstly, for the attributes which did not be matched with keywords, the matching is performed by the ontology, and then utilize the improved semantic similarity formula to match the attributes that did not be matched in the first two steps, at last successfully matching attributes construct final query interface and established the query mapping. This paper presents a Deep Web interface integration approach of Chinese books area. The attributes integrated by this method are comprehensive and it is applicable to the structured, semi-structured, unstructured and mixed query interfaces. Experiment results show that our approach can achieve higher attribute matching accuracy.