Friday 19th of April 2024
 

An Efficient Cluster Based Web Object Filters From Web Pre-Fetching And Web Caching On Web User Navigation


A. K. Santra and S. Jayasudha

The World Wide Web is a distributed internet system, which provides dynamic and interactive services includes on line tutoring, video/audio conferencing, e-commerce, and etc., which generated heavy demand on network resources and web servers. It increase over the past few year at a very rapidly rate, due to which the amount of traffic over the internet is increasing. As a result, the network performance has now become very slow. Web Pre-fetching and Caching is one of the effective solutions to reduce the web access latency and improve the quality of service. The existing model presented a Cluster based pre-fetching scheme identified clusters of correlated Web pages based on users access patterns. Web Pre-fetching and Caching cause significant improvements on the performance of Web infrastructure. In this paper, we present an efficient Cluster based Web Object Filters from Web Pre-fetching and Web caching scheme to evaluate the web user navigation patterns and user references of product search. Clustering of web page objects obtained from pre-fetched and web cached contents. User Navigation is evaluated from the web cluster objects with similarity retrieval in subsequent user sessions. Web Object Filters are built with the interpretation of the cluster web pages related to the unique users by discarding redundant pages. Ranking is done on users web page product preferences at multiple sessions of each individual user. The performance is measured in terms of Objective function, Number of clusters and cluster accuracy.

Keywords: Web usage mining, web mining, web log files, Web Proxy

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ABOUT THE AUTHORS

A. K. Santra
A. K. Santra received the P. G. degree and Doctorate degree from I.I.T., Kharagpur in the year 1975 and 1981 respectively. He has got 20 years of Teaching Experience and 19 years of Industrial (Research) Experience. His area of interest includes Artificial Intelligence, Neural Networks, Process Modeling, Optimization and Control. He has got to his credit (i) 45 Technical Research Papers which are published in National / International Journals and Seminars of repute, (ii) 20 Research Projects have been completed in varied application areas, (iii) 2 Copy Rights for Software Development have been obtained in the area of Artificial Neural Networks (ANN) and (iv) he is the contributor of the book entitled “Mathematics and its Applications in Industry and Business”, Narosa Publishing House, New Delhi. He is the recognized Supervisor for guiding Ph. D. / M. S. (By Research) Scholars of Anna University-Chennai, Anna University-Coimbatore, Bharathiyar University, Coimbatore and Mother Teresa University, Kodaikanal. Currently he is guiding 12 Ph. D. Research Scholars in the Department. He is a Life member of CSI and a Life member of ISTE.

S. Jayasudha
S. Jayasudha received her M. C. A., from Periyar University, Salem, M.Phil. from Bharathidasan University, Trichy. Currently she is working as Asst.Professor in Bannari Amman Institute of Technology, Sathyamangalam. Her area of interest includes Web Mining, Text Mining. She has presented one national and one International Conference paper. She has published a research paper in International Journal (IJCSI). She is a Life member of Computer Society of India and a Life member of Indian Society for Technical Education.


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