Editore: Springer Berlin Heidelberg, 2010
ISBN 10: 3642134211 ISBN 13: 9783642134210
Lingua: Inglese
Da: Buchpark, Trebbin, Germania
Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 196 | Sprache: Englisch | Produktart: Bücher.
EUR 82,77
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 79,32
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
EUR 79,31
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloCondizione: New.
EUR 80,37
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloCondizione: New.
EUR 82,09
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
EUR 84,69
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Chiron Media, Wallingford, Regno Unito
EUR 79,02
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: New.
Editore: Springer Berlin Heidelberg Mai 2010, 2010
ISBN 10: 3642134211 ISBN 13: 9783642134210
Lingua: Inglese
Da: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Germania
EUR 106,99
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Neuware -Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means. 196 pp. Englisch.
Editore: Springer Berlin Heidelberg Mai 2010, 2010
ISBN 10: 3642134211 ISBN 13: 9783642134210
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 106,99
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Neuware -Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means. 196 pp. Englisch.
Editore: Springer Berlin Heidelberg, 2012
ISBN 10: 3642263496 ISBN 13: 9783642263491
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 106,99
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means.
Editore: Springer Berlin Heidelberg Mai 2010, 2010
ISBN 10: 3642134211 ISBN 13: 9783642134210
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 106,99
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Neuware - Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 119,31
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 119,31
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: California Books, Miami, FL, U.S.A.
EUR 130,10
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg Mai 2010, 2010
ISBN 10: 3642134211 ISBN 13: 9783642134210
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 106,99
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Neuware -Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch.
Editore: Springer-Verlag New York Inc, 2012
ISBN 10: 3642263496 ISBN 13: 9783642263491
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
EUR 152,88
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 2010 edition. 182 pages. 9.00x6.00x0.25 inches. In Stock.
Editore: Springer-Verlag New York Inc, 2010
ISBN 10: 3642134211 ISBN 13: 9783642134210
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
EUR 154,36
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 200 pages. 9.20x6.30x0.60 inches. In Stock.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 104,86
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 105,20
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Editore: Springer Berlin Heidelberg Jun 2012, 2012
ISBN 10: 3642263496 ISBN 13: 9783642263491
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 106,99
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means. 196 pp. Englisch.
Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg Jun 2012, 2012
ISBN 10: 3642263496 ISBN 13: 9783642263491
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 106,99
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Mining social networks has now becoming a very popular research area not only for data mining and web mining but also social network analysis. Data mining is a technique that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of social communications and social networking websites, data mining becomes a very important and powerful technique to process and analyze such large amount of data. Thus, this book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that presented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book. The chapters of this book are introduced as follows: In chapter 1-Graph Model for Pattern Recognition in Text, Qin Wu et al. present a novel approach that uses a weighted directed multigraph for text pattern recognition. In the proposed methodology, a weighted directed multigraph model has been set up by using the distances between the keywords as the weights of arcs as well a keyword-frequency distance based algorithm has also been introduced. Case studies are also included in this chapter to show the performance is better than traditional means.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch.
Editore: Springer-Verlag New York Inc, 2010
ISBN 10: 3642134211 ISBN 13: 9783642134210
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
EUR 138,39
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 200 pages. 9.20x6.30x0.60 inches. In Stock. This item is printed on demand.