Resource Selection & Integration of Data on Deep Web

Most web structures are huge, intricate and users often miss the purpose of their inquest, or get uncertain results when they try to navigate through them. Internet is enormous compilation of multivariate data. Several problems prevent effective and efficient knowledge discovery for required better knowledge management techniques it is important to retrieve accurate and complete data. The hidden web, also known as the invisible web or deep web, has given rise to a novel issue of web mining research. a huge amount documents in the hidden web, as well as pages hidden behind search forms, specialized databases, and dynamically generated web pages, are not accessible by universal web mining application. in this research we proposed a approach is designed that has a robust ability to access these hidden web techniques for better invisible web resources selection and integration system. In this research we using SC technique for invisible web resources selection and integration and its construction for real-world domains based on database schemas clustering, web searching interfaces and improve traditional methods for information retrieve. Applications of our proposed system include invisible web query interface mapping and intelligent user query intension recognition based on our domain knowledge-base.