Discovering Deep Web Interfaces Using Data Mining Approach

Computer Engineering

The content hidden behind HTML forms, has long been Recognized as a significant gap in search engine coverage. It represents required contents of the data on the Web; accessing Deep-Web content is not an easy challenge for the database community. Indexing of the searched data is fundamental problem faced by web crawlers that has profound effect on search engine efficiency. Recent study about searching contents on the web shows that nearly 96% of data over internet is encapsulated as well as hidden i.e. not found to search engines. The challenge faced by the search engines is to retrieve and access hidden web data or contents at low cost. This composed system uses a machine learning approach that is highly scalable, completely automatic, and very efficient to use, that helps to improve data retrieval functionality at lower cost. This system uses focused crawling strategy for accessing accurate searched results related to query and selects only relevant information or data according to their similarity with respect to query. The algorithm used in this system intelligently selects only possible candidates rather than searching whole document for inclusion in too your web search index.

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