Earticle

초록

영어

Information content plays an important role in measuring semantic similarity of concepts. The conventional way of IC obtained is through statistical analysis of corpora. Recently corpora–independent model has attracted great concern in this area. This paper analyzes the state-of-art IC models, highlights important related issues, and presents a novel IC model based on concepts’ topology in WordNet. Different from previous work, for a given concept, the depth itself, the number of its hyponyms, and the depth of every hyponym have been taken into considered. Experiment demonstrates that our approach is able to provide more accurate similarity evaluation and achieves significant performance than related works.

목차

Abstract
 1. Introduction
 2. Related Work
  2.1. Information Content-based Similarity Measures
  2.2. IC Model
 3. A New Model of Information Content Based on Concepts’ Topology
 4. Evaluation
  4.1. Dataset
  4.2. Words Similarity Calculating Method
  4.3. Results Analysis
 5. Discussion and Future Work
 Reference

키워드

저자

• Lingling Meng1 [ Computer Science and Technology Department, Department of Educational Information Technology, East China Normal University ]
• Junzhong Gu [ Computer Science and Technology Department, East China Normal University ]
• Zili Zhou [ College of Physics and Engineering, Qufu Normal University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605