著者

中山 浩太郎 伊藤 雅弘 Maike ERDMANN 白川 真澄 道下 智之 原 隆浩 西尾 章治郎

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.24, no.6, pp.549-557, 2009 (Released:2009-10-20)

参考文献数

25

被引用文献数

5 4 2

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Wikipedia, a collaborative Wiki-based encyclopedia, has become a huge phenomenon among Internet users. It covers a huge number of concepts of various fields such as arts, geography, history, science, sports and games. As a corpus for knowledge extraction, Wikipedia's impressive characteristics are not limited to the scale, but also include the dense link structure, URL based word sense disambiguation, and brief anchor texts. Because of these characteristics, Wikipedia has become a promising corpus and a new frontier for research. In the past few years, a considerable number of researches have been conducted in various areas such as semantic relatedness measurement, bilingual dictionary construction, and ontology construction. Extracting machine understandable knowledge from Wikipedia to enhance the intelligence on computational systems is the main goal of "Wikipedia Mining," a project on CREP (Challenge for Realizing Early Profits) in JSAI. In this paper, we take a comprehensive, panoramic view of Wikipedia Mining research and the current status of our challenge. After that, we will discuss about the future vision of this challenge.

著者

中山 浩太郎 伊藤 雅弘 ERDMANN Maike 白川 真澄 道下 智之 原 隆浩 西尾 章治郎

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.24, no.6, pp.549-557, 2009

被引用文献数

3 4

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Wikipedia, a collaborative Wiki-based encyclopedia, has become a huge phenomenon among Internet users. It covers a huge number of concepts of various fields such as arts, geography, history, science, sports and games. As a corpus for knowledge extraction, Wikipedia's impressive characteristics are not limited to the scale, but also include the dense link structure, URL based word sense disambiguation, and brief anchor texts. Because of these characteristics, Wikipedia has become a promising corpus and a new frontier for research. In the past few years, a considerable number of researches have been conducted in various areas such as semantic relatedness measurement, bilingual dictionary construction, and ontology construction. Extracting machine understandable knowledge from Wikipedia to enhance the intelligence on computational systems is the main goal of "Wikipedia Mining," a project on CREP (Challenge for Realizing Early Profits) in JSAI. In this paper, we take a comprehensive, panoramic view of Wikipedia Mining research and the current status of our challenge. After that, we will discuss about the future vision of this challenge.

著者

中山 浩太郎 伊藤 雅弘 Erdmann Maike 白川 真澄 道下 智之 原 隆浩 西尾 章治郎

出版者

情報処理学会

雑誌

情報処理学会論文誌データベース(TOD) (ISSN:18827799)

巻号頁・発行日

vol.2, no.4, pp.49-60, 2009-12-24

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Wikipediaは,インターネットを通じて誰でも編集可能なオンライン百科事典であり,ここ数年で爆発的に成長したソーシャルメディアの一種である.特に,自然言語,人工知能,データベースの研究分野で活発に研究が進められており,連想関係抽出や,対訳辞書構築,オントロジ構築など,数多くのWikipediaを対象とした研究が行われてきた.また,最近では多様なアプリケーションへWikipediaマイニングの成果を適用する事例が報告されており,その有用性が示されてきた.しかし,多量の研究発表が行われる一方で,全体像を把握することが困難になりつつあるのも事実である.本サーベイ論文では,これら最新のWikipedia研究を紹介しつつ,概観することで研究の目的面・技術面から分類し,Wikipedia研究の動向を探る.Wikipedia, an Wiki based online encycropedia, has become an emergent social media because of the significant effeciency for sharing huge amount of human knowledge via Web browsers. Especially, in NLP, AI and DB research areas, a considerable number of researches have been conducted in past several years. Relatedness measurement, bilingual dictionary extraction and ontology construction are ones of main Wikipedia Mining research areas. Furthermore, researches on application based on structured data extracted by Wikipedia Mining are becoming one of the essentials of Wikipedia research areas. In this survey paper, we introduce the new research papers and summarize the researches from both technical aspect and directional aspect.