A fuzzy based semantic search engine for document retrieval in a personalized data space

Classifying the content oriented search in a personalized document-space often becomes inconvenient and inconsistent due to the need to reach the actual want of the user. The traditional search tools consider the query as it is and hence imposes on restrictions in collecting the relevant data. This work proposes a fuzzy based content search in which the scoring of content is gathered from inverse document frequency mechanism. The queries are fuzzified and also involved in scoring part of information retrieval to explore the users' real component of interest in the query.

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