A Survey on Clustering Algorithms for web Applications
نویسندگان
چکیده
Web page clustering techniques categorize & organize search results into semantically meaningful clusters that assist users to search relevant information quickly. In general, it provides a solution for data management, information locating & interpretation of web data. Also facilitate users for discrimination, navigation & organization of web pages. Finding information on the World Wide Web is one of the most popular activities of Internet users. Due to increasing amount of information on the web, it has become very important to organize this large amount of information into meaningful clusters. Clustering is currently one of the most crucial techniques for dealing, with massive amount of heterogeneous information on the web. Unlike clustering in other fields, web page clustering separates unrelated pages and clusters related pages of a specific topic into one group. This paper gives an idea about Web Page rank algorithms like HITS (Hyperlink Induced Topic Search); page Rank, & Web page clustering algorithms like STC (Suffix Tree Clustering), Vivisimo Algorithm, Lingo algorithm with their advantages & Disadvantages.
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