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Agglomerative Clustering in Web Usage Mining: A Survey
Author(s) -
Karuna Katariya,
Rajanikanth Aluvalu
Publication year - 2014
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/15523-4306
Subject(s) - computer science , hierarchical clustering , cluster analysis , data mining , world wide web , data science , information retrieval , artificial intelligence
Usage Mining used to extract knowledge from WWW. Nowadays interaction of user towards web data is growing, web usage mining is significant in effective website management, adaptive website creation, support services, personalization, and network traffic flow analysis and user trend analysis and user's profile also helps to promote website in ranking. Agglomerative clustering is a most flexible method and it is also used for clustering the web data in web usage mining, there are do not need the number of clusters as a input. Agglomerative have many drawbacks such as initial error propagation, dimensionality, complexity and data set size issues. In this paper we have introduced solution for data set size problem that helpful for information retrieve from large web data, web log data files are as a input for agglomerative clustering algorithms and output is efficient clustering that will be used further for information extraction in web usage mining.

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