A fast density-based data stream clustering algorithm with cluster centers self-determined for mixed data-Reference-Cited by-同舟云学术

A fast density-based data stream clustering algorithm with cluster centers self-determined for mixed data

Published:2016-06 Issue: Volume:345 Page:271-293
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Chen Jin-Yin^ORCID,He Hui-Hao

Funder

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference30 articles.

1. Clustering by fast search and find of density peaks;Alex;Science,2014

2. A framework for clustering evolving data streams;Aggarwal,2003

3. A framework for projected clustering of high dimensional data streams;Aggarwal,2004

4. A k-mean clustering algorithm for mixed numeric and categorical data;Amir;Data Knowl. Eng.,2007

5. Categorical fuzzy k-modes clustering with automated feature weight learning;Arkajyoti;Neurocomputing,2015

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