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Volume & Issue no: Volume 3, Issue 12, December 2014

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Title:
Lucid Gumption Maturation with Query Constellation and Data Retrieval
Author Name:
Dr. Brijesh Khandelwal, Dr. S. Q. Abbas
Abstract:
ABSTRACT This research work will be strengthening my ongoing study of Information Retrieval performance Refinement in Deep Web Mining. The information explosion on the Internet has placed high demands on search engines. Yet people are far from being satisfied with the performance of the existing search engines, which often return thousands of documents in response to a user query. Many of the returned documents are irrelevant to the user s need. The precision of current search engines is well under people s expectations. The problem of gumption indistinctness is also one of the reasons of poor performance of the search engines. Deep Web clustering engines have been proposed as one of the solution to the lexical indistinctness issue in Deep Web Information Retrieval. These systems group search results, by providing a cluster for each specific aspect (i.e., meaning) of the input query. Users can then select the cluster(s) and the pages therein that best answer their information needs. The paper tries to discover the success level of query clustering approach for the gumption indistinctness problem in web information retrieval. The extension with annotated framed interface can be exercised for better retrieval of information from deep web too. Furtherance to it, the introduction of logical deep web data retrieval services carries great potential for information retrieval. Keywords- Query Constellation, Gumption Lucidity, Similarity measure, Web data, Deep Web Access
Cite this article:
Dr. Brijesh Khandelwal, Dr. S. Q. Abbas , " Lucid Gumption Maturation with Query Constellation and Data Retrieval" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 3, Issue 12, December 2014 , pp. 239-244 , ISSN 2319 - 4847.
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