Earticle

초록

영어

Calculating semantic similarity between concepts in ontology is an important issue in natural language processing and so on, so how to measure the similarity becomes a hot topic among many scholars. However, most existing methods cannot distinguish the similarity further. Confronting this problem, we propose a new semantic similarity method combining hierarchy structure of ontology and information content of two concepts based on domain ontology, which highlights the semantic information of leaves in the ontology structure. Our experiment demonstrates that, compared with other available methods, our proposal can improve the accuracy between two leaves and between leaf and non-leaf.

목차

Abstract
 1. Introduction
 2. Concept Similarity Measure with Hierarchy Structure and Information
  2.1. Relevant Definitions
  2.2. Hierarchy Structure in Ontology
  2.3. Information Content in Ontology
  2.4. Integration of Hierarchy Structure and Information Content
 3. Experiment
  3.1. Test Datasets and Setting of Relevant Parameters
  3.2. Evaluation and Analysis
 4. Conclusion
 Acknowledgements
 References

키워드

저자

• Cong Dai [ School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China ]
• Dongmei Li [ School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China ]
• Hui han [ School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China ]
• Qichen Han [ University of Chinese Academy of Sciences, College of Engineering & Information Technology, Beijing, 100049, China ]
• Jiajia Hou [ School of Information, Renmin University of China, Beijing100872, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605