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    Social Computing: A Data Mining Perspective
      • GET 10% OFF

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      • Publisher's listprice GBP 44.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        22 769 Ft (21 685 Ft + 5% VAT)
      • Discount 10% (cc. 2 277 Ft off)
      • Discounted price 20 492 Ft (19 517 Ft + 5% VAT)

    22 769 Ft

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    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Edition number 1
    • Publisher Chapman and Hall
    • Date of Publication 1 January 2021

    • ISBN 9781420083309
    • Binding Hardback
    • No. of pages300 pages
    • Size 234x156 mm
    • Language English
    • Illustrations 30 Illustrations, black & white
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    Short description:

    This book begins with a brief introduction to social computing and a review of classic graph theory and game theory. It then examines the data used to construct social networks, focusing on emerging Web 2.0 technologies and social networking websites, such as Facebook and MySpace. The book also explores data mining for social network extraction and analysis, presenting link and graph mining algorithms, such as subgraph discovery and clustering. In the last section, the authors provide case studies to illustrate concepts and principles as well as to demonstrate how to integrate components in order to solve real-world problems.

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    Long description:

    This book begins with a brief introduction to social computing and a review of classic graph theory and game theory. It then examines the data used to construct social networks, focusing on emerging Web 2.0 technologies and social networking websites, such as Facebook and MySpace. The book also explores data mining for social network extraction and analysis, presenting link and graph mining algorithms, such as subgraph discovery and clustering. In the last section, the authors provide case studies to illustrate concepts and principles as well as to demonstrate how to integrate components in order to solve real-world problems.

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