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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/4445

Title: DESIGN A PERCEPTION BASED SEMANTICS MODEL FOR KNOWLEDGE EXTRACTION
Keywords: WSD, NLP, semantic measures, Information Retrieval, User Perception
Researcher: Sunita
Guide(s): Dr Vijay Rana (Co-Supervisor)
Registration Date: 7-8-2017
Abstract: World Wide Web needs to discover meaning of certain textual resources in order to semantically describe the result. This vision is more complicated because current search engine focus only on retrieving the documents containing the user keywords, and lots of data that may carry the desired semantic information remains overdue. So in these circumstances WSD and NLP plays an important role to retrieve valuable information from the web. The current scenario demands the delegation of intelligence of Web to smaller but more intelligent communities of components known as WSD and NLP. The Web is working in highly heterogeneous environment in term of semantic heterogeneity and redundancy issue. In fact, achieving the interoperability between dissimilar information retrieval systems is extremely tedious, complex and error-prone task. Most of the existing search systems are not able to retrieve the desired results with their intended meaning and this is primarily due to the fact that these systems have not been designed with the intention of extracting wisdom from the web. The need for research activities in Web and enhancements by developing a standard, flexible but intelligent, adaptive and distributed framework for the support of heterogeneous infrastructure is apparent. This research study is to develop flexible information specific model which exploits information available on the web adequately. The result is based on SPBS is to improve the results efficiency; SPBS is the change in user preference from manipulations of seek outcome by search engine providers. Our Model re-ranking search results manipulate according to user perception. Information extraction enables the generic extraction and minimizes re-processing of data. Due to, this provides automated query generation mechanism so that, casual users no need to learn the query language in order to perform mining. The function of this model is to extract the information based on user input. newline
Language: English
Appears in Department:Department of Computer Science Application

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