Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
