Robust Clustering for Tracking Noisy Evolving Data Streams

被引：0

作者：

Nasraoui, Olfa ^{[1
]}

Rojas, Carlos ^{[1
]}

机构：

[1] Univ Louisville, Dept Comp Engn & Comp Sci, Speed Sch Engn, Louisville, KY 40292 USA

来源：

PROCEEDINGS OF THE SIXTH SIAM INTERNATIONAL CONFERENCE ON DATA MINING | 2006年

关键词：

evolving data streams; robust clustering; dynamic clustering; stream clustering; scalable clustering;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a new approach for tracking evolving and noisy data streams by estimating clusters based on density, while taking into account the possibility of the presence of an unknown amount of outliers, the emergence of new patterns, and the forgetting of old patterns.

引用

页码：619 / 623

页数：5

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