Topic analysis using a finite mixture model.

DOI10.1016/S0306-4573(02)00035-3zbMath1035.68093OpenAlexW2066733218MaRDI QIDQ1400359

Kenji Yamanishi, Hang Li

Publication date: 13 August 2003

Published in: Information Processing and Management (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0306-4573(02)00035-3

zbMATH Keywords

Mixture modelStatistical learningText segmentationTopicWord clustering

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Natural language processing (68T50)

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