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WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles: 4th International Workshop, Edmonton, Canada, July 23, 2002, Revised Papers: 2703 - Brossura
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1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that - dress the unique challenges of discovering insights from Web usage data, aiming toevaluateWebusability,understandtheinterestsandexpectationsofusersand assess the e?ectiveness of content delivery. The maturing and expanding Web presents a key driving force in the rapid growth of electronic commerce and a new channel for content providers. Customized o?ers and content, made possible by discovered knowledge about the customer, are fundamental for the establi- ment of viable e-commerce solutions and sustained and e?ective content delivery in noncommercial domains. Rich Web logs provide companies with data about their online visitors and prospective customers, allowing microsegmentation and personalized interactions. While Web mining as a domain is several years old, the challenges that characterize data analysis in this area continue to be formidable. Though p- processing data routinely takes up a major part of the e?ort in data mining, Web usage data presents further challenges based on the di?culties of assigning data streams to unique users and tracking them over time. New innovations are required to reliably reconstruct sessions, to ascertain similarity and di?erences between sessions, and to be able to segment online users into relevant groups.
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Contenuti
LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition.- Mining eBay: Bidding Strategies and Shill Detection.- Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models.- Web Usage Mining by Means of Multidimensional Sequence Alignment Methods.- A Customizable Behavior Model for Temporal Prediction of Web User Sequences.- Coping with Sparsity in a Recommender System.- On the Use of Constrained Associations for Web Log Mining.- Mining WWW Access Sequence by Matrix Clustering.- Comparing Two Recommender Algorithms with the Help of Recommendations by Peers.- The Impact of Site Structure and User Environment on Session Reconstruction in Web Usage Analysis.
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WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles : 4th International Workshop, Edmonton, Canada, July 23, 2002, Revised Papers
Editore:
Springer Berlin Heidelberg, 2003
ISBN 10: 3540203044
ISBN 13: 9783540203049
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Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that - dr. Codice articolo 4884574
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WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that - dress the unique challenges of discovering insights from Web usage data, aiming toevaluateWebusability,understandtheinterestsandexpectationsofusersand assess the e ectiveness of content delivery. The maturing and expanding Web presents a key driving force in the rapid growth of electronic commerce and a new channel for content providers. Customized o ers and content, made possible by discovered knowledge about the customer, are fundamental for the establi- ment of viable e-commerce solutions and sustained and e ective content delivery in noncommercial domains. Rich Web logs provide companies with data about their online visitors and prospective customers, allowing microsegmentation and personalized interactions. While Web mining as a domain is several years old, the challenges that characterize data analysis in this area continue to be formidable. Though p- processing data routinely takes up a major part of the e ort in data mining, Web usage data presents further challenges based on the di culties of assigning data streams to unique users and tracking them over time. New innovations are required to reliably reconstruct sessions, to ascertain similarity and di erences between sessions, and to be able to segment online users into relevant groups. 196 pp. Englisch. Codice articolo 9783540203049
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WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles: 4th International Workshop, Edmonton, Canada, July 23, 2002, Revised Papers (Lecture Notes in Computer Science, 2703)
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Paperback. Condizione: Very Good. Springer, 2003; First Paperback Printing with full number line; vii, 179pp. Spine is uncreased, binding tight and sturdy; text, illustrations also very good; minor wear to edges of wraps. Ships from Dinkytown in Minneapolis, Minnesota. Codice articolo 284219
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WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles : 4th International Workshop, Edmonton, Canada, July 23, 2002, Revised Papers
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ISBN 10: 3540203044
ISBN 13: 9783540203049
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that - dress the unique challenges of discovering insights from Web usage data, aiming toevaluateWebusability,understandtheinterestsandexpectationsofusersand assess the e ectiveness of content delivery. The maturing and expanding Web presents a key driving force in the rapid growth of electronic commerce and a new channel for content providers. Customized o ers and content, made possible by discovered knowledge about the customer, are fundamental for the establi- ment of viable e-commerce solutions and sustained and e ective content delivery in noncommercial domains. Rich Web logs provide companies with data about their online visitors and prospective customers, allowing microsegmentation and personalized interactions. While Web mining as a domain is several years old, the challenges that characterize data analysis in this area continue to be formidable. Though p- processing data routinely takes up a major part of the e ort in data mining, Web usage data presents further challenges based on the di culties of assigning data streams to unique users and tracking them over time. New innovations are required to reliably reconstruct sessions, to ascertain similarity and di erences between sessions, and to be able to segment online users into relevant groups. Codice articolo 9783540203049
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Taschenbuch. Condizione: Neu. Neuware -1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that - dress the unique challenges of discovering insights from Web usage data, aiming toevaluateWebusability,understandtheinterestsandexpectationsofusersand assess the e ectiveness of content delivery. The maturing and expanding Web presents a key driving force in the rapid growth of electronic commerce and a new channel for content providers. Customized o ers and content, made possible by discovered knowledge about the customer, are fundamental for the establi- ment of viable e-commerce solutions and sustained and e ective content delivery in noncommercial domains. Rich Web logs provide companies with data about their online visitors and prospective customers, allowing microsegmentation and personalized interactions. While Web mining as a domain is several years old, the challenges that characterize data analysis in this area continue to be formidable. Though p- processing data routinely takes up a major part of the e ort in data mining, Web usage data presents further challenges based on the di culties of assigning data streams to unique users and tracking them over time. New innovations are required to reliably reconstruct sessions, to ascertain similarity and di erences between sessions, and to be able to segment online users into relevant groups.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch. Codice articolo 9783540203049
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WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles: 4th International Workshop, Edmonton, Canada, July 23, 2002, Revised Papers (Volume 2703)
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Condizione: New. This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Mining Web Data, WEBKDD 2002, held in Edmonton, Canada, in July 2002.The 10 revised full papers presented together with a detailed preface went through two rounds of reviewing and improvement and were selected from 23 submissions. Editor(s): Zaiane, Osmar R.; Srivastava, Jaideep; Spiliopoulou, Myra; Masand, Brij. Series: Lecture Notes in Computer Science. Num Pages: 183 pages, biography. BIC Classification: UDB. Category: (G) General (US: Trade); (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 233 x 155 x 10. Weight in Grams: 283. . 2003. 2003rd Edition. paperback. . . . . Codice articolo V9783540203049
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