Earticle

초록

영어

In this paper, we present the ideas and methodologies on labeling the mentioned entities with the wiki dataset. This paper presents a system for the recognition and semantic disambiguation of named entities based on information extracted from a large encyclopedic collection from Wikipedia. We focus on maximizing the similarity between the contextual information extracted from Wikipedia and the context of a document, as well as the similarity among the category tags associated with the candidate entities. Our experimental results show that the proposed methods are effective and efficient to answer complex named entities disambiguation over the Wikipedia dataset.

목차

Abstract
 1. Introduction
 2. Related Work
 3. The General Framework for Named Entity Disambiguation
 4. Entity Detecting, Data Preprocessing, and Entity Linking
  4.1 Entity Detecting and Data Processing
  4.2 Entity Linking
 5. Performance Evaluation
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Yongbo Yu [ School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, China ]
• Lizhou Zheng [ School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, China ]
• Kaifang Yang [ School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, China ]
• Peiquan Jin [ School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605