مشاهده مشخصات مقاله
Identification of Web Communities using Cellular Learning Automata
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نویسنده (ها) |
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
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 over 3 billion pages and it is still growing
very fast, identification of web communities has
become an increasingly hard task. In this paper, a
method based on asynchronous cellular learning
automata (ACLA) for identification of web
communities is proposed. In the proposed method
first an asynchronous cellular learning automaton
is used to determine the related pages and their
relevance degree (the relationship structure of web
pages). For determination of relationship structure
of web pages information about hyperlinks and the
users’ behaviour in visiting the web pages are
used. Then, an algorithm similar to the HITS
algorithm is applied on the obtained structure to
identify the web communities. One of the
advantages of the proposed method is that the web
community obtained using this method is not
dependent on a specific web graph structure. To
evaluate the proposed approach, it is implemented
and the results are compared with the results
obtained for two existing methods, HITS and a
complete bipartite graph based method.
Experimental results show the superiority of the
proposed method. |
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قیمت |
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برای اعضای سایت : ۱٠٠,٠٠٠ ریال
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برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
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برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
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