Applying a burst model to detect bursty topics in a topic model

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7614 LNAI, Issue , 2012, Pages 239-249

  Takahashi, Yusuke ^a   Utsuro, Takehito ^a   Yoshioka, Masaharu ^b   Kando, Noriko ^c   Fukuhara, Tomohiro ^d   Nakagawa, Hiroshi ^e   Kiyota, Yoji ^f  

^a UNIVERSITY OF TSUKUBA   (Japan)

^b HOKKAIDO UNIVERSITY   (Japan)

^c NATIONAL INSTITUTE OF INFORMATICS   (Japan)

^d NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

^e UNIVERSITY OF TOKYO   (Japan)

^f Next International Co Ltd   (Japan)

Author keywords

Kleinberg's Burst Model; Time Series News; Topic Model

Indexed keywords

BURST MODELS; BURSTY TOPICS; DOCUMENT COLLECTION; INFORMATION FLOWS; LATENT DIRICHLET ALLOCATION; TOPIC MODEL;

NATURAL LANGUAGE PROCESSING SYSTEMS; STATISTICS; TEMPERATURE CONTROL; TIME SERIES ANALYSIS;

INFORMATION SERVICES;

EID: 84868143749     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33983-7_24     Document Type: Conference Paper

References (7)

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