Research And Application On Technology Of Deep Web Schema Acquisition

Rapid development of Internet witnesses web information is growing at an unprecedented rate. A great amount of information called as Deep Web has been deepened in myriad searchable database online and is accessible only by filling out HTML form to query. Deep Web is a promising topic to study and has been paid more and more attention. This paper firstly focuses on technology of Deep Web schema acquisition. According to the schema knowledge learnt, we propose relevant algorithm and model to perform task of Deep Web data extraction. Finally Deep Web object-level vertical search system is presented.The main work is summarized as following:(1) Introduce relevant knowledge of Deep Web and its related research work, then propose main framework and corresponding difficulties.(2) Analyse the technology of vision-based page segment, and propose a new method of Deep Web interface schema extraction and Deep Web result schema extraction.(3) Study on Deep Web schema matching, then propose a composite matching strategy and corresponding algorithm. The domain-specific global schema is constructed accordingly.(4) Propose an approach of schema-based Wrapper generation for Deep Web data extraction, and briefly explain technology of Wrapper maintenance.(5) Introduce a new technology of vertical search, and integrate subsystems above to design a Deep Web object-level vertical search system.Finally this paper designs experiment to implement the algorithms and technology mentioned. Experimental results testify that our solution could achieve accurately and effectively.