Art

J-GLOBAL ID：201902274981206750   Reference number：19A1318645

Story co-segmentation of Chinese broadcast news using weakly-supervised semantic similarity

弱教師付き意味類似性を用いた中国語放送ニュースの物語共セグメンテーション【JST・京大機械翻訳】

Author (8)： Feng Wei (School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China) ,  Feng Wei (Key Research Center for Surface Monitoring and Analysis of Cultural Relics, State Administration of Cultural Heritage, China) ,  Nie Xuecheng (Department of Electrical and Computer Engineering, National University of Singapore, Singapore) ,  Zhang Yujun (School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China) ,  Zhang Yujun (Key Research Center for Surface Monitoring and Analysis of Cultural Relics, State Administration of Cultural Heritage, China) ,  Liu Zhi-Qiang (School of Creative Media, City University of Hong Kong, Hong Kong, China) ,  Dang Jianwu (School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China) ,  Dang Jianwu (School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Japan)
Material： Neurocomputing
Volume： 355  Page： 121-133  Publication year： 2019 
JST Material Number： W0360A  ISSN： 0925-2312  Document type： Article
Article type： 原著論文  Country of issue： Netherlands (NLD)  Language： ENGLISH (EN)

Abstract/Point： This paper presents lexical st...

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Thesaurus term： semantics ,  *broadcast(telecommunication) ,  corpus ,  graph ,  benchmark ,  *segmentation ,  *similarity ,  effectiveness ,  vocabulary ,  Gibbs free energy ,  *news ,  *Chinese ,  measure ,  word ,  model

Author keywords (6)： Story co-segmentation ,  Weakly-supervised correlated affinity graph (WSCAG) ,  Parallel affinity propagation ,  Generalized cosine similarity ,  Chinese broadcast news ,  MRF

JST classification (1)： Pattern recognition  (JE07000S)

Terms in the title (7)： 教師 ,  意味類似性 ,  中国語 ,  放送 ,  ニュース ,  物語 ,  セグメンテーション