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2008

A novel self-organising clustering model for time-event documents

9 years 3 months ago
A novel self-organising clustering model for time-event documents
Purpose Neural document clustering techniques, e.g., self-organising map (SOM) or growing neural gas (GNG), usually assume that textual information is stationary on the quantity. However, the quantity of text is ever-increasing. We propose a novel dynamic adaptive self-organising hybrid (DASH) model, which adapts to time-event news collections not only to the neural topological structure but also to its main parameters in a non-stationary environment. Design/methodology/approach
Chihli Hung, Stefan Wermter
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where EL
Authors Chihli Hung, Stefan Wermter
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