9783709102930-3709102936-From Sociology to Computing in Social Networks: Theory, Foundations and Applications (Lecture Notes in Social Networks)

From Sociology to Computing in Social Networks: Theory, Foundations and Applications (Lecture Notes in Social Networks)

ISBN-13: 9783709102930
ISBN-10: 3709102936
Edition: 2010
Author: Reda Alhajj, Nasrullah Memon
Publication date: 2010
Publisher: Springer
Format: Hardcover 449 pages
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Book details

ISBN-13: 9783709102930
ISBN-10: 3709102936
Edition: 2010
Author: Reda Alhajj, Nasrullah Memon
Publication date: 2010
Publisher: Springer
Format: Hardcover 449 pages

Summary

From Sociology to Computing in Social Networks: Theory, Foundations and Applications (Lecture Notes in Social Networks) (ISBN-13: 9783709102930 and ISBN-10: 3709102936), written by authors Reda Alhajj, Nasrullah Memon, was published by Springer in 2010. With an overall rating of 3.5 stars, it's a notable title among other Computer Science books. You can easily purchase or rent From Sociology to Computing in Social Networks: Theory, Foundations and Applications (Lecture Notes in Social Networks) (Hardcover) from BooksRun, along with many other new and used Computer Science books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Important aspects of social networking analysis are covered in this work by combining experimental and theoretical research. A specific focus is devoted to emerging trends and the industry needs associated with utilizing data mining techniques. Some of the techniques covered include data mining advances in the discovery and analysis of communities, in the personalization of solitary activities (like searches) and social activities (like discovering potential friends), in the analysis of user behavior in open fora (like conventional sites, blogs and fora) and in commercial platforms (like e-auctions), and in the associated security and privacy-preservation challenges; as well as social network modeling, scalable, customizable social network infrastructure construction, and the identification and discovery of dynamic growth and evolution patterns using machine learning approaches or multi-agent based simulation. These topics will be of interest to practitioners and researchers alike in this dynamic and growing field.
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