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Item Details
| Title:
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PREDICTING REAL WORLD BEHAVIORS FROM VIRTUAL WORLD DATA
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| By: |
Muhammad Aurangzeb Ahmad (Editor), Cuihua Shen (Editor), Jaideep Srivastava (Editor) |
| Format: |
Paperback |
| List price:
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£62.99 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
3319348493 |
| ISBN 13: |
9783319348490 |
| Publisher: |
SPRINGER INTERNATIONAL PUBLISHING AG |
| Pub. date: |
24 September, 2016 |
| Edition: |
Softcover reprint of the original 1st ed. 2014 |
| Series: |
Springer Proceedings in Complexity |
| Pages: |
118 |
| Synopsis: |
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. |
| Illustrations: |
49 Tables, black and white; 27 Illustrations, color; 13 Illustrations, |
| Publication: |
Switzerland |
| Imprint: |
Springer International Publishing AG |
| Returns: |
Non-returnable |
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