Adaptive Resonance Theory in Social Media Data Clustering: Roles, Methodologies, and Applications

by Lei Meng, Ah-Hwee Tan, Donald C. Wunsch II

Social media data contains our communication and online sharing, mirroring our daily life. This book looks at how we can use and what we can discover from such big Adaptive Resonance Theory in Social Media Data Clustering stands on the fundamental breakthrough in cognitive and neural theory, i.e. adaptive resonance theory, which simulates how a brain processes information to perform memory, learning, recognition, and prediction. It presents initiatives on the mathematical demonstration of ART’s learning mechanisms in clustering, and illustrates how to extend the base ART model to handle the complexity and characteristics of social media data and perform associative analytical tasks. Both cutting-edge research and real-world practices on machine learning and social media analytics are included in the book and if you wish to learn the answers to the following questions, this book is for
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205 pages, Hardcover

Published May 14, 2019