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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...
Different efforts have been made to address the problem of information overload on the Internet. Web recommendation systems based on web usage mining try to mine users' behavior patterns from web access logs, and recommend pages to the online user by matching the user's browsing behavior with the mined historical behavior patterns. In this paper we propose effective and scalable technique to solve...
A important phase in any Web personalization system is transaction identification. Recently a number of researches have been done to incorporate semantics of a website in representation of transactions. Building a hierarchy of concepts manually is time consuming and expensive. In this paper we intend to address these shortcomings. Our contribution is that we introduce a mechanism to automatically...
Clustering is currently one of the most crucial techniques for dealing with massive amount of heterogeneous information on the web, which is beyond human beingpsilas capacity to digest. Recent studies have shown that the most commonly used partitioning-based clustering algorithm, the K-means algorithm, is more suitable for large datasets. However, the K-means algorithm can generate a local optimal...
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