인터넷정보학회논문지 (Journal of Internet Computing and Services)

  • 제18권3호
  • /
  • Pages.49-61
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  • 2017
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  • 1598-0170(pISSN)
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  • 2287-1136(eISSN)
한국인터넷정보학회 (Korean Society for Internet Information)
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An effective approach to generate Wikipedia infobox of movie domain using semi-structured data

  • Bhuiyan, Hanif (Dept. of Computer Science & Information Engineering Inha University) ;
  • Oh, Kyeong-Jin (Dept. of Computer Science & Information Engineering Inha University) ;
  • Hong, Myung-Duk (Dept. of Computer Science & Information Engineering Inha University) ;
  • Jo, Geun-Sik (Dept. of Computer Science & Information Engineering Inha University)
  • 투고 : 2017.02.10
  • 심사 : 2017.04.25
  • 발행 : 2017.06.30
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초록

Wikipedia infoboxes have emerged as an important structured information source on the web. To compose infobox for an article, considerable amount of manual effort is required from an author. Due to this manual involvement, infobox suffers from inconsistency, data heterogeneity, incompleteness, schema drift etc. Prior works attempted to solve those problems by generating infobox automatically based on the corresponding article text. However, there are many articles in Wikipedia that do not have enough text content to generate infobox. In this paper, we present an automated approach to generate infobox for movie domain of Wikipedia by extracting information from several sources of the web instead of relying on article text only. The proposed methodology has been developed using semantic relations of article content and available semi-structured information of the web. It processes the article text through some classification processes to identify the template from the large pool of template list. Finally, it extracts the information for the corresponding template attributes from web and thus generates infobox. Through a comprehensive experimental evaluation the proposed scheme was demonstrated as an effective and efficient approach to generate Wikipedia infobox.

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참고문헌

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피인용 문헌

  1. 지식베이스 구축을 위한 한국어 위키피디아의 학습 기반 지식추출 방법론 및 플랫폼 연구 vol.25, pp.1, 2019, https://doi.org/10.13088/jiis.2019.25.1.043