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Title: Content Retrieval Framework for Web Sources using Text Mining
Authors: Mekala, A.
Asanka, B.D.
Keywords: Web Mining
Web Content Mining
Data Mining
Association Rule
Information Extraction
Issue Date: 26-Sep-2014
Series/Report no.: PNCTM;22
Abstract: This research describes a framework to find out the most relevant information related to web sources according to the users’ preferences. Literature survey has identified that existing search engines did not return the accurate results. To overcome this issue, the research pulled out most accurate results to be returned according to users search criteria using text mining technique. This framework aims to identify the relevant web sources to crawl the specified information using web crawlers, in order to build the necessary dataset. The analysis is two folded as Web contents and Web content’s titles. The created data set is passed to generate keywords. These keywords have taken to apply “Association Rule” data mining technique to train and then to be verified using test data to ensure the accuracy of the developed framework. The research result show most relevant Web URLs related to users’ search. These results are directed to analyze how web source will be of better use for Web content mining framework such as Web contents or content’s titles.
Description: SLIIT Research
ISSN: 1800-3591
Appears in Collections:NCTM - SLIIT 2014 -JANUARY

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