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- W2183630073 abstract "A collection of web pages which are about a common topic and are created by individuals or any kind of associations that have a common interest on that specific topic is called a web community. Since at present, the size of the web is about 3 billion pages and it is still growing very fast, identification of web communities has become an increasingly hard task. In this paper, we used distributed learning Automata and mining association rules to identify we communities. Our proposed method is the same [1] that uses distributed learning automata and mining association rules to calculate hub and authority scores of web pages, which causes most cases unrelated to the topic, as members of the community web pages not considered. Our proposed method, are compared with the approaches of [1] and [2], and the results show that the our proposed is efficient." @default.
- W2183630073 created "2016-06-24" @default.
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- W2183630073 date "2013-01-01" @default.
- W2183630073 modified "2023-09-24" @default.
- W2183630073 title "Identification of Web Communities Using Distributed Learning Automata and Association Rules Mining" @default.
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