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Volumn , Issue , 2013, Pages 109-117

A Weakly Supervised Bayesian Model for Violence Detection in Social Media

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; SOCIAL NETWORKING (ONLINE);

EID: 85064115573     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (18)

References (26)
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    • Andrzejewski, David1    Zhu, Xiaojin2    Craven, Mark3
  • 2
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    • Supervised topic models
    • D.M. Blei and J. McAuliffe. 2008. Supervised topic models. In NIPS, 20:121–128.
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    • Learning from labeled features using generalized expectation criteria
    • G. Druck, G. Mann, and A. McCallum. 2008. Learning from labeled features using generalized expectation criteria. In SIGIR, pages 595–602.
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    • Druck, G.1    Mann, G.2    McCallum, A.3
  • 6
    • 36348939917 scopus 로고    scopus 로고
    • Overcoming the brittleness bottleneck using Wikipedia: enhancing text categorization with encyclopedic knowledge
    • Evgeniy Gabrilovich and Shaul Markovitch. 2006. Overcoming the brittleness bottleneck using Wikipedia: enhancing text categorization with encyclopedic knowledge. In AAAI.
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    • Gabrilovich, Evgeniy1    Markovitch, Shaul2
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    • Joint sentiment/topic model for sentiment analysis
    • C. Lin and Y. He. 2009. Joint sentiment/topic model for sentiment analysis. In CIKM, pages 375–384.
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    • Lin, C.1    He, Y.2
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    • D. Mimno and A. McCallum. 2008. Topic models conditioned on arbitrary features with dirichlet-multinomial regression. In UAI.
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    • Mimno, D.1    McCallum, A.2
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    • Aspect extraction through semi-supervised modeling
    • Arjun Mukherjee and Bing Liu. 2012. Aspect extraction through semi-supervised modeling. In ACL, pages 339–348.
    • (2012) ACL , pp. 339-348
    • Mukherjee, Arjun1    Liu, Bing2
  • 22
    • 57349117605 scopus 로고    scopus 로고
    • Learning to classify short and sparse text and web with hidden topics from large-scale data collections
    • X. H. Phan, L. M. Nguyen, and S. Horiguchi. 2008. Learning to classify short and sparse text and web with hidden topics from large-scale data collections. In WWW.
    • (2008) WWW
    • Phan, X. H.1    Nguyen, L. M.2    Horiguchi, S.3
  • 23
    • 80053392186 scopus 로고    scopus 로고
    • Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora
    • D. Ramage, D. Hall, R. Nallapati, and C.D. Manning. 2009. Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora. In EMNLP, pages 248–256.
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    • Earthquake shakes twitter users: real-time event detection by social sensors
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    • Short text conceptualization using a probabilistic knowledgebase
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.