Web Usage Mining Using Discovered Frequent Pattern Algorithms

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61,90 

Basics, Steps, Rules, and comparison about algorithms of extracting frequent patterns

ISBN: 3659786861
ISBN 13: 9783659786860
Autor: Soleimani, Farid/Ataei, Elnaz
Verlag: LAP LAMBERT Academic Publishing
Umfang: 132 S.
Erscheinungsdatum: 26.10.2015
Auflage: 1/2015
Format: 0.9 x 22 x 15
Gewicht: 215 g
Produktform: Kartoniert
Einband: Kartoniert
Artikelnummer: 8752343 Kategorie:

Beschreibung

Developing word of the web and increasing the content information, web site users requirements has been changed. Therefore web needs a dynamic and accurate algorithm to recognize users 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 users. 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.

Autorenporträt

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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