Synopsis
The book is composed of seven chapters. Chapter 1 gives an introduction to web usage mining. In this research work, some approaches are developed to predict the users' behaviour from weblogIn this chapter, the background and motivation for this research work are explained. Chapter 1 describes the organization of the book. The related works in this area are discussed in Chapter 2. An existing literature survey includes the user behaviour prediction, frequent pattern mining, high utility and top-k HUIM itemset mining from weblog. Chapter 3 describes preprocessing techniques applied for weblog and also describes a pattern mining approach for SNS. Chapter 4 describes a high utility itemsets from weblog. High utility itemset refers to those set of items which has high utility such as profit in a database. Chapter 5 describes rare itemset mining from weblog. Chapter 6 explains the top-k high utility itemsets mining named TKHUIM for mining most high utility itemsets and it is based on frequent pattern mining. Chapter 7 concludes the book and also discussed the future enhancements. In this chapter, the outcome of this research work is explained.
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Efficient Techniques for Patterns Analysis using Web Usage Mining
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book is composed of seven chapters. Chapter 1 gives an introduction to web usage mining. In this research work, some approaches are developed to predict the users' behaviour from weblogIn this chapter, the background and motivation for this research work are explained. Chapter 1 describes the organization of the book. The related works in this area are discussed in Chapter 2. An existing literature survey includes the user behaviour prediction, frequent pattern mining, high utility and top-k HUIM itemset mining from weblog. Chapter 3 describes preprocessing techniques applied for weblog and also describes a pattern mining approach for SNS. Chapter 4 describes a high utility itemsets from weblog. High utility itemset refers to those set of items which has high utility such as profit in a database. Chapter 5 describes rare itemset mining from weblog. Chapter 6 explains the top-k high utility itemsets mining named TKHUIM for mining most high utility itemsets and it is based on frequent pattern mining. Chapter 7 concludes the book and also discussed the future enhancements. In this chapter, the outcome of this research work is explained. 88 pp. Englisch. Seller Inventory # 9786139858712
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Efficient Techniques for Patterns Analysis using Web Usage Mining
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bakariya BrijeshBrijesh Bakariya Assistant Professor in Department of Computer Science and Engineering,IKGPTU, Jalandhar (Punjab) has his Ph. D. Degree from NIT- Bhopal, MP in Computer Applications (2016). He has been teaching sinc. Seller Inventory # 385874608
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Efficient Techniques for Patterns Analysis using Web Usage Mining
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LAP LAMBERT Academic Publishing Jun 2018, 2018
ISBN 10: 6139858712
ISBN 13: 9786139858712
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book is composed of seven chapters. Chapter 1 gives an introduction to web usage mining. In this research work, some approaches are developed to predict the users' behaviour from weblogIn this chapter, the background and motivation for this research work are explained. Chapter 1 describes the organization of the book. The related works in this area are discussed in Chapter 2. An existing literature survey includes the user behaviour prediction, frequent pattern mining, high utility and top-k HUIM itemset mining from weblog. Chapter 3 describes preprocessing techniques applied for weblog and also describes a pattern mining approach for SNS. Chapter 4 describes a high utility itemsets from weblog. High utility itemset refers to those set of items which has high utility such as profit in a database. Chapter 5 describes rare itemset mining from weblog. Chapter 6 explains the top-k high utility itemsets mining named TKHUIM for mining most high utility itemsets and it is based on frequent pattern mining. Chapter 7 concludes the book and also discussed the future enhancements. In this chapter, the outcome of this research work is explained.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch. Seller Inventory # 9786139858712
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Efficient Techniques for Patterns Analysis using Web Usage Mining
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book is composed of seven chapters. Chapter 1 gives an introduction to web usage mining. In this research work, some approaches are developed to predict the users' behaviour from weblogIn this chapter, the background and motivation for this research work are explained. Chapter 1 describes the organization of the book. The related works in this area are discussed in Chapter 2. An existing literature survey includes the user behaviour prediction, frequent pattern mining, high utility and top-k HUIM itemset mining from weblog. Chapter 3 describes preprocessing techniques applied for weblog and also describes a pattern mining approach for SNS. Chapter 4 describes a high utility itemsets from weblog. High utility itemset refers to those set of items which has high utility such as profit in a database. Chapter 5 describes rare itemset mining from weblog. Chapter 6 explains the top-k high utility itemsets mining named TKHUIM for mining most high utility itemsets and it is based on frequent pattern mining. Chapter 7 concludes the book and also discussed the future enhancements. In this chapter, the outcome of this research work is explained. Seller Inventory # 9786139858712
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Efficient Techniques for Patterns Analysis using Web Usage Mining
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Taschenbuch. Condition: Neu. Efficient Techniques for Patterns Analysis using Web Usage Mining | Brijesh Bakariya (u. a.) | Taschenbuch | 88 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139858712 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 114094447
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