Predicting real world behaviors from virtual world data / Muhammad Aurangzeb Ahmad, Cuihua Shen, Jaideep Srivastava, Noshir Contractor, editors.
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...
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| Online Access: |
Full Text (via Springer) |
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| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer,
2014.
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| Series: | Springer proceedings in complexity.
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| Subjects: |
| Summary: | 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. |
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| Physical Description: | 1 online resource (xiv, 118 pages) : illustrations (some color) |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9783319071428 3319071424 3319071416 9783319071411 |
| ISSN: | 2213-8684. |
| Source of Description, Etc. Note: | Source of description: Online resource; title from PDF title page (SpringerLink, viewed August 6, 2014) |