Identifying pairs of terms with strong semantic connections in a textbook index

James Geller, Shmuel T. Klein, Yuriy Polyakov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Semantic relationships are important components of ontologies. Specifying these relationships is workintensive and error-prone when done by experts. Discovering domain concepts and strongly related pairs of concepts in a completely automated way from English text is an unresolved problem. This paper uses index terms from a textbook as domain concepts and suggests pairs of concepts that are likely to be connected by strong semantic relationships. Two textbooks on Cyber Security were used as testbeds. To show the generality of the approach, the index terms from one of the books were used to generate suggestions for where to place semantic relationships using the bodies of both textbooks. A good overlap was found.

Original languageEnglish
Title of host publicationKEOD
EditorsAna Fred, Jan Dietz, David Aveiro, Kecheng Liu, Joaquim Filipe
Pages307-315
Number of pages9
ISBN (Electronic)9789897581588
DOIs
StatePublished - 2015
Event7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015 - Lisbon, Portugal
Duration: 12 Nov 201514 Nov 2015

Publication series

NameIC3K 2015 - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
Volume2

Conference

Conference7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015
Country/TerritoryPortugal
CityLisbon
Period12/11/1514/11/15

Keywords

  • Ontology
  • Security Concepts
  • Semantic Relationships
  • Semantically Correlated Terms
  • Textbook Index

All Science Journal Classification (ASJC) codes

  • Software

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