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

• Κύριοι συγγραφείς: Meng, Lei (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Tan, Ah-Hwee (http://id.loc.gov/vocabulary/relators/aut), Wunsch II, Donald C. (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: Advanced Information and Knowledge Processing,
• Θέματα: Data mining.; Algorithms.; Cognitive psychology.; Pattern recognition.; Data Mining and Knowledge Discovery.; Algorithm Analysis and Problem Complexity.; Cognitive Psychology.; Pattern Recognition.

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 data: Basic knowledge (data & challenges) on social media analytics Clustering as a fundamental technique for unsupervised knowledge...

Πίνακας περιεχομένων:

• Part 1: Theories
• Introduction
• Clustering and Extensions in the Social Media Domain
• Adaptive Resonance Theory (ART) for Social Media Analytics
• Part II: Applications
• Personalized Web Image Organization
• Socially-Enriched Multimedia Data Co-Clustering
• Community Discovery in Heterogeneous Social Networks
• Online Multimodal Co-Indexing and Retrieval of Social Media Data
• Concluding Remarks.