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ERIC Number: EJ670084
Record Type: Journal
Publication Date: 2003
Pages: N/A
Abstractor: N/A
Reference Count: N/A
ISBN: N/A
ISSN: ISSN-0306-4573
Topic Analysis Using a Finite Mixture Model.
Li, Hang; Yamanishi, Kenji
Information Processing & Management, v39 n4 p521-41 Jul 2003
Presents a single framework for conducting topic analysis that performs both topic identification and text segmentation. Key characteristics of the framework are: representing a topic by means of a cluster of words closely related to the topic; and employing a stochastic model, called a finite mixture model, to represent a word distribution within a text. (AEF)
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A