- 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
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.