Predicting Real World Behaviors from Virtual World Data

Lieferzeit: Lieferbar innerhalb 14 Tagen

53,49 

Springer Proceedings in Complexity

ISBN: 3319071416
ISBN 13: 9783319071411
Herausgeber: Muhammad Aurangzeb Ahmad/Cuihua Shen/Jaideep Srivastava et al
Verlag: Springer Verlag GmbH
Umfang: xiv, 118 S., 13 s/w Illustr., 27 farbige Illustr., 118 p. 40 illus., 27 illus. in color.
Erscheinungsdatum: 07.08.2014
Auflage: 1/2014
Produktform: Gebunden/Hardback
Einband: GEB

This book addresses prediction, mining and analysis of offline characteristics and behaviors from online data and vice versa. Each chapter will focus on a different aspect of virtual worlds to real world prediction e.g., demographics, personality, location, etc.There is a growing body of literature that focuses on the similarities and differences between how people behave in the offline world vs. how they behave in these virtual environments. Data mining has aided in discovering interesting insights with respect to how people behave in these virtual environments.

Artikelnummer: 6592979 Kategorie:

Beschreibung

There is a growing body of literature that focuses on the similarities and differences between how people behave in the offline world vs. how they behave in these virtual environments. Data mining has aided in discovering interesting insights with respect to how people behave in these virtual environments. The book addresses prediction, mining and analysis of offline characteristics and behaviors from online data and vice versa. Each chapter will focus on a different aspect of virtual worlds to real world prediction e.g., demographics, personality, location, etc.

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