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Web Log Preprocessing and Fuzzy Pattern Discovery - Zahid Ansari

Anglų
2017-09-27
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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. Anothe ... Visas aprašymas

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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 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.

Daugiau informacijos

Autorius Zahid Ansari
Leidėjas LAP LAMBERT Academic Publishing
Išleidimo metai 2017
Viršelio tipas Minkšti viršeliai
EAN 9786202050234
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53,86 € 71,81 €