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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)
  • Received : 2021.01.05
  • Published : 2021.01.30

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

References

  1. 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
  2. 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
  3. 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
  4. 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\
  5. 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
  6. Bouayad-Agha, N., Casamayor, G., &Wanner, L. (2014). Natural Language Generation in the context of the Semantic Web. Semantic Web, 5, 493-513. https://doi.org/10.3233/SW-130125
  7. 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. https://doi.org/10.1007/s11280-010-0087-z
  8. 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. \
  9. Bojars, U., Liepins, R., Gruzitis, N., Cerans, K., &Celms, E. (2016). Extending OWL Ontology Visualizations with Interactive Contextual Verbalization. VOILA@ISWC.
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. Mann, W.C., & Thompson, S.A. (1988). Rhetorical Structure Theory: Toward a functional theory of text organization. Text & Talk, 8, 243 - 281.
  17. 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
  18. 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
  19. 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
  20. Poulovassilis, A., Selmer, P., & Wood, P. T. (2016). Approximation and Relaxation of Semantic Web Path Queries. SSRN ElectronicJournal. doi:10.2139/ssrn.3199265
  21. 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
  22. 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
  23. 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
  24. Singh, A., Ramasubramanian, K., & Shivam, S. (2019). Introduction to Microsoft Bot, RASA, and Google Dialogflow.
  25. 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.
  26. Ralston, K. (2019). Personalizing Chatbot Conversations with IBM Watson.
  27. Wallace, The Elements of AIML Style, ALICE A. I. Foundation, Inc. March 28, 2003
  28. Wallace, R. S. (2014). AIML 2.0 Working Draft, https://docs.google.com/document/d/1wNT25hJRyup cG51aO89UcQEiG-HkXRXusukADpFnDs4/pub