Web Log Preprocessing and Fuzzy Pattern Discovery - Ansari, Zahid
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This book presents methods, approaches and techniques to perform the main tasks of Web log preprocessing that include Data Cleaning, Web user identification and extraction of user sessions. In order to accomplish the dimensionality reduction and trim down the adverse effect of outliers, a fuzzy set theoretic approach for assigning fuzzy weights to user sessions and associated URLs has been described. Another main part discussed in this book is the analysis of the Web server log file preprocessing results and discovery of user session clusters using Fuzzy c-Means algorithm. Mainly this book is…mehr

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Produktbeschreibung
This book presents methods, approaches and techniques to perform the main tasks of Web log preprocessing that include Data Cleaning, Web user identification and extraction of user sessions. In order to accomplish the dimensionality reduction and trim down the adverse effect of outliers, a fuzzy set theoretic approach for assigning fuzzy weights to user sessions and associated URLs has been described. Another main part discussed in this book is the analysis of the Web server log file preprocessing results and discovery of user session clusters using Fuzzy c-Means algorithm. Mainly this book is suitable for researchers who are interested in the preprocessing techniques of web log data for Web usage mining applications such as Web personalization, website design, business intelligence etc.
Autorenporträt
O Dr. Zahid Ansari é Professor do CSE e Reitor (Investigação) no PA College of Engineering, Mangalore, Índia. Anteriormente foi associado ao Tata Consultancy Services R&D Center, Pune, GE-Harris Melbourne, Florida USA e USAA, San Antonio Texas USA. Publicou 2 livros e mais de 75 artigos em várias revistas e conferências internacionais de renome.