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Creators/Authors contains: "Kim, Y. and"

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  1. ; ; ; ; ; ; (, 26th Asia and South Pacific Design Automation Conference (ASP-DAC))
    Accepted Manuscript Full Text Available
  2. (, Proceedings of the European Conference on Information Retrieval)
    Alerting users that a web page is controversial has been proposed as one method to support critical thinking about text and discourse. We propose an approach to discover controversial topics in a generic document using unsupervised training. Our approach comprises iterative training of a controversy classifier using a disagreement signal within comments and explaining the controversy of the document by generating a topic phrase describing it. Experiments show the effectiveness of our proposed training method using an EM algorithm. When controversial topic extraction is restricted to quality phrases and incorporates TextRank signals, it outperforms several baseline approaches. 
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