Sinopsis
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.
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Reseña del editor
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.
Biografía del autor
Dr. Zahid Ansari is a Professor of CSE and Dean (Research) at PA College of Engineering, Mangaluru, India. Earlier he was associated with Tata Consultancy Services R&D Center, Pune, BARC Mumbai, GE-Harris Melbourne Florida USA and USAA, San Antonio Texas USA. He has published 55+ articles in various international journals and conferences of repute.
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Web Log Preprocessing and Fuzzy Pattern Discovery
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LAP LAMBERT Academic Publishing Sep 2017, 2017
ISBN 10: 6202050233
ISBN 13: 9786202050234
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 108 pp. Englisch. Nº de ref. del artículo: 9786202050234
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Web Log Preprocessing and Fuzzy Pattern Discovery
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ISBN 13: 9786202050234
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ansari ZahidDr. Zahid Ansari is a Professor of CSE and Dean (Research) at PA College of Engineering, Mangaluru, India. Earlier he was associated with Tata Consultancy Services R&D Center, Pune, BARC Mumbai, GE-Harris Melbourne Florid. Nº de ref. del artículo: 176461740
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Web Log Preprocessing and Fuzzy Pattern Discovery
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LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202050233
ISBN 13: 9786202050234
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Web Log Preprocessing and Fuzzy Pattern Discovery
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LAP LAMBERT Academic Publishing Sep 2017, 2017
ISBN 10: 6202050233
ISBN 13: 9786202050234
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 108 pp. Englisch. Nº de ref. del artículo: 9786202050234
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Web Log Preprocessing and Fuzzy Pattern Discovery
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9786202050234
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Web Log Preprocessing and Fuzzy Pattern Discovery
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ISBN 10: 6202050233
ISBN 13: 9786202050234
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Taschenbuch. Condición: Neu. Web Log Preprocessing and Fuzzy Pattern Discovery | Zahid Ansari | Taschenbuch | 108 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202050234 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Nº de ref. del artículo: 110094240
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