Efficient streaming text clustering

Clustering data streams has been a new research topic, recently emerged from many real data mining applications, and has attracted a lot of research attention. However, there is little work on clustering high-dimensional streaming text data. This paper combines an efficient online spherical k-means...

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Vydáno v:	Neural networks Ročník 18; číslo 5; s. 790 - 798
Hlavní autor:	Zhong, Shi
Médium:	Journal Article Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.07.2005 Elsevier Science
Témata:	Algorithms Applied sciences Cluster Analysis Competitive learning Computer science; control theory; systems Data processing. List processing. Character string processing Databases, Factual Exact sciences and technology Information theory Information, signal and communications theory Memory Memory organisation. Data processing Online Systems Signal and communications theory Signal representation. Spectral analysis Signal, noise Software Spherical k-means Streaming clustering Telecommunications and information theory Text clustering Text clustering Spherical k-means Competitive learning Streaming clustering Performance evaluation Streaming Automatic classification Adaptive algorithm Scalability Forgetting factor On-line systems Data processing K means algorithm Data mining Signal classification Information transmission Learning Database Open market
ISSN:	0893-6080, 1879-2782
On-line přístup:	Získat plný text
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