Web Usage Mining Using Discovered Frequent Pattern Algorithms | Basics, Steps, Rules, and comparison about algorithms of extracting frequent patterns
Farid Soleimani (u. a.)
ISBN 10: 3659786861 ISBN 13: 9783659786860
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Web Usage Mining Using Discovered Frequent Pattern Algorithms | Basics, Steps, Rules, and comparison about algorithms of extracting frequent patterns | Farid Soleimani (u. a.) | Taschenbuch | 132 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659786860 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 104156065
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Developing word of the web and increasing the content information, web site user’s requirements has been changed. Therefore web needs a dynamic and accurate algorithm to recognize user’s requirements to suggest new patterns. Web mining helps to solve the problem of discovering how users are using Web sites. It involves mining logs (or log analysis) and the steps that typically have to be gone through to get meaningful data from Web logs - data collection, pre-processing, data enrichment and pattern analysis and discovery. This book presents methods, approaches and techniques to perform three main tasks of web usage mining (Preprocessing, Pattern discovery and Pattern analysis). In another part of book discussed techniques of WUM to design Web recommender systems and shown that how WUM can be applied to Web server logs for discovering access patterns. The important part of this book discussed about static and dynamic algorithms that build path tree and extract frequent pattern of web user’s. Finally the dynamic algorithm compared together such as CATS-tree, AFPIM, CAN-tree, CP-tree and I-FARM, In terms of time complexity and executed speed.
About the Author: Authors:Farid Soleimani, M.sc: computer software engineering. Young Researcher and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran.Elnaz Ataei, M.A: Accounting. Department of Sciences, Ardabil Branch, Islamic Azad University, Ardabil, Iran.
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Title: Web Usage Mining Using Discovered Frequent ...
Publisher: LAP LAMBERT Academic Publishing
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Developing word of the web and increasing the content information, web site user¿s requirements has been changed. Therefore web needs a dynamic and accurate algorithm to recognize user¿s requirements to suggest new patterns. Web mining helps to solve the problem of discovering how users are using Web sites. It involves mining logs (or log analysis) and the steps that typically have to be gone through to get meaningful data from Web logs - data collection, pre-processing, data enrichment and pattern analysis and discovery. This book presents methods, approaches and techniques to perform three main tasks of web usage mining (Preprocessing, Pattern discovery and Pattern analysis). In another part of book discussed techniques of WUM to design Web recommender systems and shown that how WUM can be applied to Web server logs for discovering access patterns. The important part of this book discussed about static and dynamic algorithms that build path tree and extract frequent pattern of web user¿s. Finally the dynamic algorithm compared together such as CATS-tree, AFPIM, CAN-tree, CP-tree and I-FARM, In terms of time complexity and executed speed.Books on Demand GmbH, Überseering 33, 22297 Hamburg 132 pp. Englisch. Seller Inventory # 9783659786860
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Web Usage Mining Using Discovered Frequent Pattern Algorithms
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Developing word of the web and increasing the content information, web site user's requirements has been changed. Therefore web needs a dynamic and accurate algorithm to recognize user's requirements to suggest new patterns. Web mining helps to solve the problem of discovering how users are using Web sites. It involves mining logs (or log analysis) and the steps that typically have to be gone through to get meaningful data from Web logs - data collection, pre-processing, data enrichment and pattern analysis and discovery. This book presents methods, approaches and techniques to perform three main tasks of web usage mining (Preprocessing, Pattern discovery and Pattern analysis). In another part of book discussed techniques of WUM to design Web recommender systems and shown that how WUM can be applied to Web server logs for discovering access patterns. The important part of this book discussed about static and dynamic algorithms that build path tree and extract frequent pattern of web user's. Finally the dynamic algorithm compared together such as CATS-tree, AFPIM, CAN-tree, CP-tree and I-FARM, In terms of time complexity and executed speed. 132 pp. Englisch. Seller Inventory # 9783659786860
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Web Usage Mining Using Discovered Frequent Pattern Algorithms : Basics, Steps, Rules, and comparison about algorithms of extracting frequent patterns
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ISBN 10: 3659786861
ISBN 13: 9783659786860
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Developing word of the web and increasing the content information, web site user's requirements has been changed. Therefore web needs a dynamic and accurate algorithm to recognize user's requirements to suggest new patterns. Web mining helps to solve the problem of discovering how users are using Web sites. It involves mining logs (or log analysis) and the steps that typically have to be gone through to get meaningful data from Web logs - data collection, pre-processing, data enrichment and pattern analysis and discovery. This book presents methods, approaches and techniques to perform three main tasks of web usage mining (Preprocessing, Pattern discovery and Pattern analysis). In another part of book discussed techniques of WUM to design Web recommender systems and shown that how WUM can be applied to Web server logs for discovering access patterns. The important part of this book discussed about static and dynamic algorithms that build path tree and extract frequent pattern of web user's. Finally the dynamic algorithm compared together such as CATS-tree, AFPIM, CAN-tree, CP-tree and I-FARM, In terms of time complexity and executed speed. Seller Inventory # 9783659786860