A Framework for Clustering Evolving Data Streams

C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu · Very Large Data Bases Conference · 2003

Summary

A fundamentally different philosophy for data stream clustering is discussed which is guided by application-centered requirements and uses the concepts of a pyramidal time frame in conjunction with a microclustering approach.

Published: 2003-09-09
Cited by: 2,051
References: 14
DOI: https://doi.org/10.1016/b978-012722442-8/50016-1
Semantic Scholar: https://api.semanticscholar.org/CorpusID:2354576

References

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Temporal Structure Learning for Clustering Massive Data Streams in Real-TimeMichael Hahsler, Margaret H. Dunham — 2011
INFORMATION-VALUE-BASED FEATURE SELECTION ALGORITHM FOR ANOMALY DETECTION OVER DATA STREAMSXiaozhen Zhou, Shanping Li, Cheng Chang — 2014
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A Framework for Clustering Massive Text and Categorical Data StreamsCharų C. Aggarwal, Philip S. Yu — 2006
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Temporal Signature Modeling and AnalysisJiangqin Sun — 2014
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