Adaptive scaling of cluster boundaries for large-scale social media data clustering

• Main Authors: MENG, Lei, TAN, Ah-hwee, WUNSCH, Donald C.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Clustering; Big social media data; Adaptive Resonance Theory; Vigilance region; Adaptive parameter tuning; Computer and Systems Architecture; Databases and Information Systems; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/5235; https://ink.library.smu.edu.sg/context/sis_research/article/6238/viewcontent/Adaptive_Scaling_of_Cluster_Boundaries___TNNLS_2016_Preprint.pdf
• Institution: Singapore Management University

The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptiv...