Measuring prerequisite relations among concepts

Chen Liang, Zhaohui Wu, Wenyi Huang, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations

Abstract

A prerequisite relation describes a basic relation among concepts in cognition, education and other areas. However, as a semantic relation, it has not been well studied in computational linguistics. We investigate the problem of measuring prerequisite relations among concepts and propose a simple link-based metric, namely reference distance (RefD), that effectively models the relation by measuring how differently two concepts refer to each other. Evaluations on two datasets that include seven domains show that our single metric based method outperforms existing supervised learning based methods.

Original languageEnglish (US)
Title of host publicationConference Proceedings - EMNLP 2015
Subtitle of host publicationConference on Empirical Methods in Natural Language Processing
PublisherAssociation for Computational Linguistics (ACL)
Pages1668-1674
Number of pages7
ISBN (Electronic)9781941643327
DOIs
StatePublished - 2015
EventConference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Lisbon, Portugal
Duration: Sep 17 2015Sep 21 2015

Publication series

NameConference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing

Other

OtherConference on Empirical Methods in Natural Language Processing, EMNLP 2015
CountryPortugal
CityLisbon
Period9/17/159/21/15

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

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    Liang, C., Wu, Z., Huang, W., & Giles, C. L. (2015). Measuring prerequisite relations among concepts. In Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing (pp. 1668-1674). (Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d15-1193