Ontology ranking based on the analysis of concept structures

Harith Alani; Christopher Brewster

doi:10.1145/1088622.1088633

Ontology ranking based on the analysis of concept structures

Harith Alani, Christopher Brewster

Research output: Chapter in Book/Published conference output › Chapter

Abstract

In view of the need to provide tools to facilitate the re-use of existing knowledge structures such as ontologies, we present in this paper a system, AKTiveRank, for the ranking of ontologies. AKTiveRank uses as input the search terms provided by a knowledge engineer and, using the output of an ontology search engine, ranks the ontologies. We apply a number of metrics in an attempt to investigate their appropriateness for ranking ontologies, and compare the results with a questionnaire-based human study. Our results show that AKTiveRank will have great utility although there is potential for improvement.

Original language	English
Title of host publication	Proceedings of the Third International Conference on Knowledge Capture
Subtitle of host publication	K-CAP '05 : October 2-5, 2005, Banff, Alberta, Canada
Place of Publication	New York, NY (US)
Publisher	ACM
Pages	51-58
Number of pages	8
ISBN (Print)	1-59593-163-5, 978-1-59593-163-4
DOIs	https://doi.org/10.1145/1088622.1088633
Publication status	Published - Oct 2005
Event	3rd international conference on Knowledge capture - Alberta, Canada Duration: 2 Oct 2005 → 5 Oct 2005

Conference

Conference	3rd international conference on Knowledge capture
Abbreviated title	K-CAP'05
Country/Territory	Canada
City	Alberta
Period	2/10/05 → 5/10/05

Keywords

knowledge structures
ontologies
AKTiveRank
ranking
knowledge engineer
ontology search engine
ranking ontologies

Access to Document

10.1145/1088622.1088633

Cite this

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title = "Ontology ranking based on the analysis of concept structures",

abstract = "In view of the need to provide tools to facilitate the re-use of existing knowledge structures such as ontologies, we present in this paper a system, AKTiveRank, for the ranking of ontologies. AKTiveRank uses as input the search terms provided by a knowledge engineer and, using the output of an ontology search engine, ranks the ontologies. We apply a number of metrics in an attempt to investigate their appropriateness for ranking ontologies, and compare the results with a questionnaire-based human study. Our results show that AKTiveRank will have great utility although there is potential for improvement.",

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author = "Harith Alani and Christopher Brewster",

year = "2005",

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doi = "10.1145/1088622.1088633",

language = "English",

isbn = "1-59593-163-5",

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booktitle = "Proceedings of the Third International Conference on Knowledge Capture",

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note = "3rd international conference on Knowledge capture, K-CAP'05 ; Conference date: 02-10-2005 Through 05-10-2005",

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Alani, H & Brewster, C 2005, Ontology ranking based on the analysis of concept structures. in Proceedings of the Third International Conference on Knowledge Capture: K-CAP '05 : October 2-5, 2005, Banff, Alberta, Canada. ACM, New York, NY (US), pp. 51-58, 3rd international conference on Knowledge capture, Alberta, Canada, 2/10/05. https://doi.org/10.1145/1088622.1088633

TY - CHAP

T1 - Ontology ranking based on the analysis of concept structures

AU - Alani, Harith

AU - Brewster, Christopher

PY - 2005/10

Y1 - 2005/10

N2 - In view of the need to provide tools to facilitate the re-use of existing knowledge structures such as ontologies, we present in this paper a system, AKTiveRank, for the ranking of ontologies. AKTiveRank uses as input the search terms provided by a knowledge engineer and, using the output of an ontology search engine, ranks the ontologies. We apply a number of metrics in an attempt to investigate their appropriateness for ranking ontologies, and compare the results with a questionnaire-based human study. Our results show that AKTiveRank will have great utility although there is potential for improvement.

AB - In view of the need to provide tools to facilitate the re-use of existing knowledge structures such as ontologies, we present in this paper a system, AKTiveRank, for the ranking of ontologies. AKTiveRank uses as input the search terms provided by a knowledge engineer and, using the output of an ontology search engine, ranks the ontologies. We apply a number of metrics in an attempt to investigate their appropriateness for ranking ontologies, and compare the results with a questionnaire-based human study. Our results show that AKTiveRank will have great utility although there is potential for improvement.

KW - knowledge structures

KW - ontologies

KW - AKTiveRank

KW - ranking

KW - knowledge engineer

KW - ontology search engine

KW - ranking ontologies

UR - http://dl.acm.org/citation.cfm?doid=1088622.1088633

U2 - 10.1145/1088622.1088633

DO - 10.1145/1088622.1088633

M3 - Chapter

SN - 1-59593-163-5

SN - 978-1-59593-163-4

SP - 51

EP - 58

BT - Proceedings of the Third International Conference on Knowledge Capture

PB - ACM

CY - New York, NY (US)

T2 - 3rd international conference on Knowledge capture

Y2 - 2 October 2005 through 5 October 2005

ER -

Ontology ranking based on the analysis of concept structures

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