@inproceedings{513b3db4ddaa45e5a3d2442400bca98e,
title = "Identifying pairs of terms with strong semantic connections in a textbook index",
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.",
keywords = "Ontology, Security Concepts, Semantic Relationships, Semantically Correlated Terms, Textbook Index",
author = "James Geller and Klein, {Shmuel T.} and Yuriy Polyakov",
note = "Publisher Copyright: Copyright {\textcopyright} 2015 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.; 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015 ; Conference date: 12-11-2015 Through 14-11-2015",
year = "2015",
doi = "10.5220/0005615403070315",
language = "English (US)",
series = "IC3K 2015 - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management",
publisher = "SciTePress",
pages = "307--315",
editor = "Ana Fred and Jan Dietz and David Aveiro and Kecheng Liu and Joaquim Filipe and Joaquim Filipe",
booktitle = "KEOD",
}