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http://dx.doi.org/10.22937/IJCSNS.2021.21.1.6

Verifying Ontology Increments through Domain and Schema Independent Verbalization  

Vidanage, Kaneeka (Faculty of Ocean Engineering Technology and Informatics, University Malaysia Terengganu)
Noor, Noor Maizura Mohamad (Faculty of Ocean Engineering Technology and Informatics, University Malaysia Terengganu)
Mohemad, Rosmayati (Faculty of Ocean Engineering Technology and Informatics, University Malaysia Terengganu)
Bakar, Zuriana Aby (Faculty of Ocean Engineering Technology and Informatics, University Malaysia Terengganu)
Publication Information
International Journal of Computer Science & Network Security / v.21, no.1, 2021 , pp. 34-39 More about this Journal
Abstract
Collaborative ontology construction is the latest trend in developing ontologies. In this technique domain specialists and ontologists need to work together. Because of the complexity associated with ontology construction, it's done in an iterative and incremental fashion. After each iteration, an ontology increment will be produced. Current ontology increment is always an enhanced version of the previous increment. Each ontology increment has to be verified for its accuracy. Domain specialists' contribution is very significant in accomplishing this necessity. Unfortunately, non-computing domain specialists (i.e. medical doctors, bankers, lawyers) are illiterate on semantic concepts. Therefore, validating the accuracy of the ontology increment is a complex hurdle for them. This research proposes verbalization approach to address this complexity.
Keywords
Ontology-increment; Ontologists; Schema; Verbalization;
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1 Alobaid, A., Garijo, D., Poveda-Villalon, M., Santana-Perez, I., Fernandez-Izquierdo, A., & Corcho, O. (2019). Automating ontology engineering support activities with OnToology. Journal of Web Semantics, 57, 100472. doi:10.1016/j.websem.2018.09.003   DOI
2 Garijo, D. (2017). WIDOCO: A Wizard for Documenting Ontologies. Lecture Notes in Computer Science, 94-102. doi:10.1007/978-3-319-68204-4_9   DOI
3 Janarthanam, S. (2017). Hands-On Chatbots and Conversational UI Development: Build chatbots and voice user interfaces with Chatfuel, Dialogflow, Microsoft Bot Framework, Twilio, and Alexa Skills.
4 Ralston, K. (2019). Personalizing Chatbot Conversations with IBM Watson.
5 Wallace, R. S. (2014). AIML 2.0 Working Draft, https://docs.google.com/document/d/1wNT25hJRyup cG51aO89UcQEiG-HkXRXusukADpFnDs4/pub
6 Bojars, U., Liepins, R., Gruzitis, N., Cerans, K., &Celms, E. (2016). Extending OWL Ontology Visualizations with Interactive Contextual Verbalization. VOILA@ISWC.
7 Sun, Mi, Olsson, Paulsson, &Harrie. (2019). Utilizing BIM and GIS for Representation and Visualization of 3D Cadastre. ISPRS International Journal of Geo-Information, 8(11), 503. doi:10.3390/ijgi8110503   DOI
8 Mann, W.C., & Thompson, S.A. (1988). Rhetorical Structure Theory: Toward a functional theory of text organization. Text & Talk, 8, 243 - 281.
9 Motta, E., Mulholland, P., Peroni, S., d'Aquin, M., GomezPerez, J.M., Mendez, V., Zablith, F.: A novel approach to visualizing and navigating ontologies. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) The Semantic Web { ISWC 2011: 10th International Semantic Web Conference, Bonn, Germany, October 23-27, 2011
10 Bao, J., Cao, Y., Tavanapong, W., & Honavar, V. (2004). Integration of DomainSpecific and DomainIndependent Ontologies for Colonoscopy Video Database Annotation. Artificial Intelligence Research LaboratoryIowa State University
11 Wallace, The Elements of AIML Style, ALICE A. I. Foundation, Inc. March 28, 2003
12 Keet, C. M., &Khumalo, L. (2016). On the verbalization patterns of part-whole relations in isiZulu. Proceedings of the 9th International Natural Language Generation conference. doi:10.18653/v1/w16-6629   DOI
13 Sportelli, F., &Franconi, E. (2016). Formalisation of ORM Derivation Rules and Their Mapping into OWL. On the Move to Meaningful Internet Systems: OTM 2016 Conferences, 827-843. doi:10.1007/978-3-319-48472-3_52   DOI
14 KaarelKaljurand and Norbert E. Fuchs. 2007. Verbalizing owl in attempt to controlled English. In Proceedings of Third International Workshop on OWL: Experiences and Directions, Innsbruck, Austria (6th-7th June 2007), volume 258
15 Guimaraes, M. A., Zisman, R. P., & Renzi, A. B. (2019). Pharmaceutical Online Store Project: Usability, Affordances and Expectations. Advances in Intelligent Systems and Computing, 523-534. doi:10.1007/978-3-030-20040-4_47   DOI
16 Androutsopoulos, I., Lampouras, G., &Galanis, D. (2013). Generating Natural Language Descriptions from OWL Ontologies: the NaturalOWL System. Journal of Artificial Intelligence Research, 48, 671-715. doi:10.1613/jair.4017   DOI
17 Bontcheva, K., & Wilks, Y. (2004). Automatic Report Generation from Ontologies: The MIAKT Approach. Natural Language Processing and Information Systems, 324-335. doi:10.1007/978-3540-27779-8_28   DOI
18 Poulovassilis, A., Selmer, P., & Wood, P. T. (2016). Approximation and Relaxation of Semantic Web Path Queries. SSRN ElectronicJournal. doi:10.2139/ssrn.3199265   DOI
19 Saha, S., Usman, Z., Li, W., Jones, S., & Shah, N. (2019). Core domain ontology for joining processes to consolidate welding standards. Robotics and Computer-Integrated Manufacturing, 59, 417-430. doi:10.1016/j.rcim.2019.05.010   DOI
20 Singh, A., Ramasubramanian, K., & Shivam, S. (2019). Introduction to Microsoft Bot, RASA, and Google Dialogflow.
21 Bouayad-Agha, N., Casamayor, G., &Wanner, L. (2014). Natural Language Generation in the context of the Semantic Web. Semantic Web, 5, 493-513.   DOI
22 Ingram, J., & Gaskell, P. (2019). Searching for meaning: Co-constructing ontologies with stakeholders for smarter search engines in agriculture. NJAS - Wageningen Journal of Life Sciences, 100300. doi:10.1016/j.njas.2019.04.006\   DOI
23 Dai, Y., Zhang, S., Chen, J., Chen, T., and Zhang, W. Semantic Network Language Generation Based on a Semantic Networks Serialization Grammar. World Wide Web 13, 3(2010), 307-341.   DOI
24 Elgammal, A., &Turetken, O. (2015). Lifecycle Business Process Compliance Management: A Semantically-Enabled Framework. 2015 International Conference on Cloud Computing (ICCC). doi:10.1109/cloudcomp.2015.7149646   DOI
25 De Nicola, A., & Missikoff, M. (2016). A lightweight methodology for rapid ontology engineering. Communications of the ACM, 59(3), 79-86. doi:10.1145/2818359 doi:10.1093/bib/6.3.239   DOI
26 Strohmaier, M., Walk, S., PPschko, J., Lamprecht, D., Tudorache, T., Nyulas, C., ...Noy, N. F. (2013). How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects. SSRN Electronic Journal. doi:10.2139/ssrn.319903   DOI
27 Demir, S., Carberry, S., and Mccoy, K. A Discourseaware Graph-based Content Selection Framework. In Proceedings of the 6th International Natural Language Generation Conference (INLG) (2010), pp. 17-27. \
28 Dorothy, B., & S. Ramesh Kumar, B. (2018). DORBRI: An Architecture for the DoD Security Breaches Through Quantum IoT. International Conference on Computer Networks and Communication Technologies, 491-496. doi:10.1007/978-981-10-8681-6_44   DOI