Scalable Dynamic Self-Organising Maps for Mining Massive Textual Data

Traditional text clustering methods require enormous computing resources, which make them inappropriate for processing large scale data collections. In this paper we present a clustering method based on the word category map approach using a two-level Growing Self-Organising Map (GSOM). A significan...

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Bibliographische Detailangaben

Hauptverfasser:	Zhai, Yu Zheng, Hsu, Arthur, Halgamuge, Saman K.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Applied sciences Artificial intelligence Cluster Task Computer science control theory systems Connectionism. Neural networks Data processing. List processing. Character string processing Exact sciences and technology Execution Time Grid Resource Memory organisation. Data processing News Article Software Spread Factor
Online-Zugang:	Volltext
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