Many organizations, whether in the public or private sector, have begun to take advantage of the tools and techniques used for data mining. Utilizing data mining tools, these organizations are able to reveal the hidden and unknown information from available data.
Data Mining in Dynamic Social Networks and Fuzzy Systems brings together research on the latest trends and patterns of data mining tools and techniques in dynamic social networks and fuzzy systems. With these improved modern techniques of data mining, this publication aims to provide insight and support to researchers and professionals concerned with the management of expertise, knowledge, information, and organizational development.
Reviews and Testimonials
The first half of this collection describes data mining tools for social network data analysis and explores issues to consider before analyzing dynamic social network data, while the second half focuses on data mining techniques for extracting data from fuzzy systems. Topics of the 15 papers include a framework for social network data security, dynamic item set mining of Twitter posts, a semantic cloud model for optimizing mobile social networks, lane changing behavior during heavy traffic conditions, and association rule mining of a sports portal news feed.
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