DBSTexC Density-Based Spatio-Textual Clustering on Twitter

Density-based spatial clustering of applications with noise (DBSCAN) is the most commonly used density-based clustering algorithm, where it can discover multiple clusters with arbitrary shapes. DBSCAN works properly when the input data type is homogeneous, but the DBSCAN's approach may not be s...

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Bibliographic Details
Published in:	Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 pp. 23 - 26
Main Authors:	Nguyen, Minh D., Shin, Won-Yong
Format:	Conference Proceeding
Language:	English
Published:	New York, NY, USA ACM 31.07.2017
Series:	ACM Conferences
Subjects:	Computing methodologies Computing methodologies > Machine learning Computing methodologies > Machine learning > Learning paradigms Computing methodologies > Machine learning > Learning paradigms > Unsupervised learning Human-centered computing Human-centered computing > Visualization Human-centered computing > Visualization > Visualization application domains Human-centered computing > Visualization > Visualization application domains > Geographic visualization Information systems Information systems > Information retrieval Information systems > Information retrieval > Retrieval tasks and goals Information systems > Information retrieval > Retrieval tasks and goals > Clustering and classification Information systems > Information systems applications Information systems > Information systems applications > Data mining Information systems > Information systems applications > Data mining > Clustering Information systems > Information systems applications > Spatial-temporal systems
ISBN:	1450349935, 9781450349932
Online Access:	Get full text
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