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Volumn 2006, Issue , 2006, Pages 649-655

A mixture model for contextual text mining

Author keywords

Clustering; Context; Contextual text mining; EM algorithm; Mixture model; Theme pattern

Indexed keywords

ALGORITHMS; INFORMATION ANALYSIS; PROBABILITY DISTRIBUTIONS; PROGRAM DOCUMENTATION; SEMANTICS; TEXT PROCESSING;

EID: 33749551461     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1150402.1150482     Document Type: Conference Paper
Times cited : (81)

References (18)
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    • A probabilistic model for retrospective news event detection
    • Z. Li, B. Wang, M. Li, and W.-Y. Ma. A probabilistic model for retrospective news event detection. In Proceedings of SIGIR'05, pages 106-113, 2005.
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    • Li, Z.1    Wang, B.2    Li, M.3    Ma, W.-Y.4
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    • Online novelty detection on temporal sequences
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    • A probabilistic approach to spatiotemporal theme pattern mining on weblogs
    • Q. Mei, C. Liu, H. Su, and C. Zhai. A probabilistic approach to spatiotemporal theme pattern mining on weblogs. In Proceedings of WWW '06, pages 533-542, 2006.
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    • Discovering evolutionary theme patterns from text: An exploration of temporal text mining
    • Q. Mei and C. Zhai. Discovering evolutionary theme patterns from text: an exploration of temporal text mining. In Proceeding of KDD'05, pages 198-207, 2005.
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    • A cross-collection mixture model for comparative text mining
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.