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Semantic Web Mining using RDF Data
Author(s) -
Víctor Asanza,
A. Amruta
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016908022
Subject(s) - computer science , rdf , semantic web , semantic analytics , information retrieval , social semantic web , world wide web , linked data , semantic web stack
Information on the web is increasing every minute. Redundancy in information is growing rapidly. Data mining is the technique used to extract this data as per the user’s query. Technically data mining analyzing and summarizing it into useful information. Keyword search is an important tool for exploring and searching large data corpuses whose structure is either unknown, or constantly changing. So, keyword search has already been studied in the context of relational databases XML documents and more recently over graphs and RDF data. Semantic web mining aims to combine semantic web and web mining. Semantic web mining is the need of today’s redundant data. In this paper major focus is on minimizing extraction of number of pages by ranking technique. Due to which the extraction of information is done exact as query fired and the top ranked pages are shown to user. Here for this three main areas are going to use such as semantic web, ontology and RDF data.

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