SCLOPE: An algorithm for clustering data streams of categorical attributes

• Main Authors: ONG, Kok-Leong, LI, Wenyuan, NG, Wee-Keong, LIM, Ee Peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2004
• Subjects: Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/1021; https://ink.library.smu.edu.sg/context/sis_research/article/2020/viewcontent/SCLOPE__An_algorithm_for_clustering_data_streams_of_categorical_attributes.pdf
• Institution: Singapore Management University

Clustering is a difficult problem especially when we consider the task in the context of a data stream of categorical attributes. In this paper, we propose SCLOPE, a novel algorithm based on CLOPE's intuitive observation about cluster histograms. Unlike CLOPE however, our algorithm is very fast...