Collaborative ontology generation method using an ant colony optimization model

Hansaem Park; Jeungmin Lee; Kyunglag Kwon; Jongsoo Sohn; Yunwan Jeon; Sungwoo Jung; In Jeong Chung

doi:10.1007/978-981-10-1536-6_71

Collaborative ontology generation method using an ant colony optimization model

Hansaem Park, Jeungmin Lee, Kyunglag Kwon, Jongsoo Sohn, Yunwan Jeon, Sungwoo Jung, In Jeong Chung

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Ontology has been regarded as the core technology of the semantic web. However, non-experts still have difficulties in participating in ontology generation. So, the growing need for public participation in ontology generation has arisen. We propose a method in which the public may participate in ontology generation by adopting the ACO (Ant Colony Optimization) algorithm. We demonstrate that the ontology generated by the proposed method is satisfactory to justify our method: precision and recall of the ontology are about 94.44 and 99.6% respectively. The suggested method enables the construction of the semantic web environment with non-experts in the field of ontology engineering.

Original language	English
Title of host publication	Advanced Multimedia and Ubiquitous Engineering - FutureTech and MUE
Editors	Hai Jin, Young-Sik Jeong, Muhammad Khurram Khan, James J. Park
Publisher	Springer Verlag
Pages	541-549
Number of pages	9
ISBN (Print)	9789811015359
DOIs	https://doi.org/10.1007/978-981-10-1536-6_71
Publication status	Published - 2016
Event	11th International Conference on Future Information Technology, FutureTech 2016 - Beijing, China Duration: 2016 Apr 20 → 2016 Apr 22

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	393
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Other

Other	11th International Conference on Future Information Technology, FutureTech 2016
Country/Territory	China
City	Beijing
Period	16/4/20 → 16/4/22

Keywords

Ant colony optimization (ACO)
Ontology
Semantic web

ASJC Scopus subject areas

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-981-10-1536-6_71

Cite this

Park, H., Lee, J., Kwon, K., Sohn, J., Jeon, Y., Jung, S., & Chung, I. J. (2016). Collaborative ontology generation method using an ant colony optimization model. In H. Jin, Y.-S. Jeong, M. K. Khan, & J. J. Park (Eds.), Advanced Multimedia and Ubiquitous Engineering - FutureTech and MUE (pp. 541-549). (Lecture Notes in Electrical Engineering; Vol. 393). Springer Verlag. https://doi.org/10.1007/978-981-10-1536-6_71

Collaborative ontology generation method using an ant colony optimization model. / Park, Hansaem; Lee, Jeungmin; Kwon, Kyunglag et al.
Advanced Multimedia and Ubiquitous Engineering - FutureTech and MUE. ed. / Hai Jin; Young-Sik Jeong; Muhammad Khurram Khan; James J. Park. Springer Verlag, 2016. p. 541-549 (Lecture Notes in Electrical Engineering; Vol. 393).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Park, H, Lee, J, Kwon, K, Sohn, J, Jeon, Y, Jung, S & Chung, IJ 2016, Collaborative ontology generation method using an ant colony optimization model. in H Jin, Y-S Jeong, MK Khan & JJ Park (eds), Advanced Multimedia and Ubiquitous Engineering - FutureTech and MUE. Lecture Notes in Electrical Engineering, vol. 393, Springer Verlag, pp. 541-549, 11th International Conference on Future Information Technology, FutureTech 2016, Beijing, China, 16/4/20. https://doi.org/10.1007/978-981-10-1536-6_71

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title = "Collaborative ontology generation method using an ant colony optimization model",

abstract = "Ontology has been regarded as the core technology of the semantic web. However, non-experts still have difficulties in participating in ontology generation. So, the growing need for public participation in ontology generation has arisen. We propose a method in which the public may participate in ontology generation by adopting the ACO (Ant Colony Optimization) algorithm. We demonstrate that the ontology generated by the proposed method is satisfactory to justify our method: precision and recall of the ontology are about 94.44 and 99.6% respectively. The suggested method enables the construction of the semantic web environment with non-experts in the field of ontology engineering.",

keywords = "Ant colony optimization (ACO), Ontology, Semantic web",

author = "Hansaem Park and Jeungmin Lee and Kyunglag Kwon and Jongsoo Sohn and Yunwan Jeon and Sungwoo Jung and Chung, {In Jeong}",

note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media Singapore 2016. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 11th International Conference on Future Information Technology, FutureTech 2016 ; Conference date: 20-04-2016 Through 22-04-2016",

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doi = "10.1007/978-981-10-1536-6_71",

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AB - Ontology has been regarded as the core technology of the semantic web. However, non-experts still have difficulties in participating in ontology generation. So, the growing need for public participation in ontology generation has arisen. We propose a method in which the public may participate in ontology generation by adopting the ACO (Ant Colony Optimization) algorithm. We demonstrate that the ontology generated by the proposed method is satisfactory to justify our method: precision and recall of the ontology are about 94.44 and 99.6% respectively. The suggested method enables the construction of the semantic web environment with non-experts in the field of ontology engineering.

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Collaborative ontology generation method using an ant colony optimization model

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