Skip to main content
SpringerLink
Log in

Domain and Schema Independent Ontology Verbalizing

  • Conference paper
  • First Online:
Advances in Data Science, Cyber Security and IT Applications (ICC 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1098))

Included in the following conference series:

  • 689 Accesses

Abstract

The semantic web has gained vast popularity among current computer scientists and engineers, due to its remarkable attribute of machine readability and human readability. As evidence of witnessing that popularity, thousands of semantic web based knowledge models have been designed, to solve various problems emerging from different domains that are almost freely available in numerous repositories in the web. Semantic web based knowledge models also referred to as ontologies, are domain rich conceptualizations. Hence, they have been widely used to gain computational intelligence, related to areas such as medical sciences, law, management and many other disciplines. Nevertheless, the complexity associated with semantic web-based knowledge representations such as RDF and OWL act as a serious bottleneck in reusability and knowledge dissemination linked with the semantic web. Knowledge retrieval from an existing ontology solely depends on schematics understanding and writing of appropriate SPARQL or SQWRL queries. This would become a really challenging hurdle for non-computer specialists such as medical consultants, lawyers, criminologists who also wish to experience the benefits of semantic web-based technologies.

This research emphasizes on proposing a generalized verbalizer which could act as domain and schema independent ontology verbalizer for both RDF and OWL ontologies in human readable English. It is expected this generic verbalizer will widen the horizons of the semantic web-based technologies by opening new ventures for non-technical audiences.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Kashyap, V.: Ontologies and schemas. In: The Semantic Web, pp. 79–135. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540764526_5

  2. Protege: Protege (2019). https://protege.stanford.edu/. Accessed 16 Feb 2019

  3. Caldarola, E.G., Rinaldi, A.M.: An approach to ontology integration for ontology reuse. In: 2016 IEEE 17th International Conference on Information Reuse and Integration (IRI) (2016). https://doi.org/10.1109/iri.2016.58

  4. Davis, I.: vocab.org - A URI space for vocabularies (2014). http://vocab.org/. Accessed 16 Feb 2019

  5. Yu, L.: Swoogle. In: Introduction to the Semantic Web and Semantic Web Services, pp. 145–157 (2007). https://doi.org/10.1201/9781584889342.pt3

    Chapter  Google Scholar 

  6. Vandenbussche, P., Atemezing, G.A., Poveda-Villalón, M., Vatant, B.: Linked Open Vocabularies (LOV): a gateway to reusable semantic vocabularies on the Web. Semantic Web 8(3), 437–452 (2016). https://doi.org/10.3233/sw-160213

    Article  Google Scholar 

  7. Musen, M.A., The Protégé Team: Protégé Ontology Editor. Encyclopedia of Systems Biology, pp. 1763–1765 (2013). https://doi.org/10.1007/978-1-4419-9863-7_1104

    Chapter  Google Scholar 

  8. Slater, L., Gkoutos, G.V., Schofield, P.N., Hoehndorf, R.: Using AberOWL for fast and scalable reasoning over BioPortal ontologies. J. Biomed. Semant. 7(1) (2016). https://doi.org/10.1186/s13326-016-0090-0

  9. National Center for Biomedical Ontology: NCBO BioPortal (2005). https://bioportal.bioontology.org/ontologies. Accessed 16 Feb 2019

  10. Spasic, I., Ananiadou, S., McNaught, J., Kumar, A.: Text mining and ontologies in biomedicine: making sense of raw text. Brief. Bioinform. 6(3), 239–251 (2005). https://doi.org/10.1093/bib/6.3.239

    Article  Google Scholar 

  11. Zenuni, X., Raufi, B., Ismaili, F., Ajdari, J.: State of the art of semantic web for healthcare. Procedia Soc. Behav. Sci. 195, 1990–1998 (2015). https://doi.org/10.1016/j.sbspro.2015.06.213

    Article  Google Scholar 

  12. Trokanas, N., Cecelja, F.: Ontology evaluation for reuse in the domain of Process Systems Engineering. Comput. Chem. Eng. 85, 177–187 (2016). https://doi.org/10.1016/j.compchemeng.2015.12.003

    Article  Google Scholar 

  13. Chergui, W., Zidat, S., Marir, F.: An approach to the acquisition of tacit knowledge based on an ontological model. J. King Saud Univ. Comput. Inf. Sci. (2018). https://doi.org/10.1016/j.jksuci.2018.09.0129

    Article  Google Scholar 

  14. Alavi, M., Leidner, D.E.: Knowledge management and knowledge management systems: conceptual foundations and research issues. Manag. Inf. Syst. Q. 25, 107–136 (2001). https://doi.org/10.2307/3250961

    Article  Google Scholar 

  15. Anderson, J.R.: The Architecture of Cognition. Harvard University Press, Cambridge (1983)

    Google Scholar 

  16. Gutierrez-Basulto, V., Ibanez-Garcia, Y., Kontchakov, R., Kostylev, E.V.: Queries with negation and inequalities over lightweight ontologies. SSRN Electron. J. (2015). https://doi.org/10.2139/ssrn.3199213

    Article  Google Scholar 

  17. Ku, C., Leroy, G.: A decision support system: automated crime report analysis and classification for egovernment. Gov. Inf. Q. 31(4), 534–544 (2014). https://doi.org/10.1016/j.giq.2014.08.003

    Article  Google Scholar 

  18. Pinheiro, V., Furtado, V., Pequeno, T., Nogueira, D.: Natural Language Processing based on Semantic inferentialism for extracting crime information from text. In: 2010 IEEE International Conference on Intelligence and Security Informatics (2010)

    Google Scholar 

  19. Rusu, D., Dali, L., Fortuna, B., Grobelnik, M., Mladnnic, D.: Triple Extraction from sentences. Paper presented at Technical University of Cluj-Napoca, Romania

    Google Scholar 

  20. Williams, S., Third, A., Power, R.: Levels of organisation in ontology verbalization. ENLG (2011). https://www.semanticscholar.org/paper/Levels-of-organisation-in-ontology-verbalisation-WilliamsThird/08c6a058f5f78cf49701d2534bf9c6af3683f9e9

  21. Habernal, I., Konopík, M.: SWSNL: semantic web search using natural language. Expert Syst. Appl. 40(9), 3649–3664 (2013). https://doi.org/10.1016/j.eswa.2012.12.070

    Article  Google Scholar 

  22. Poulovassilis, A., Selmer, P., Wood, P.T.: Approximation and relaxation of semantic web path queries. SSRN Electr. J. (2016). https://doi.org/10.2139/ssrn.3199265

  23. Kaljurand, K., Fuchs, N.E.: Verbalizing owl in attempt to controlled English. In: Proceedings of Third International Workshop on OWL: Experiences and Directions, Innsbruck, Austria (6th–7th June 2007), vol. 258 (2007)

    Google Scholar 

  24. Bontcheva, K., Wilks, Y.: Automatic report generation from ontologies: the MIAKT approach. Nat. Lang. Process. Inf. Syst., 324–335 (2004). https://doi.org/10.1007/978-3-540-27779-8_28

    Chapter  Google Scholar 

  25. Bao, J., Cao, Y., Tavanapong, W., Honavar, V.: Integration of domain-specific and domain-independent ontologies for colonoscopy video database annotation. Artificial Intelligence Research Laboratory-Iowa State University (2004)

    Google Scholar 

  26. Bojars, U., Liepins, R., Gruzitis, N., Cerans, K., Celms, E.: Extending OWL Ontology Visualizations with Interactive Contextual Verbalization. VOILA@ISWC (2016)

    Google Scholar 

  27. Smith, N., Flanagan, C.: The Effective Detective: Identifying the skills of an effective SIO. Police Research Series (2000). http://library.college.police.uk/docs/hopolicers/fprs122.pdf

  28. Noy, N., McGuiness, D.: Ontology Development 101: A Guide to Creating Your First Ontology. Stanford University, Stanford (2001)

    Google Scholar 

  29. El Ghosh, M., Naja, H., Abdulrab, H., Khalil, M.: Towards a legal rule-based system grounded on the integration of criminal domain ontology and rules. Procedia Comput. Sci. 112, 632–642 (2017). https://doi.org/10.1016/j.procs.2017.08.109

    Article  Google Scholar 

  30. Rose, S., Engel, D., Cramer, N., Cowley, W.: Automatic keyword extraction from individual documents. Text Mining 1, 1–20 (2010). https://doi.org/10.1002/9780470689646.ch1

    Google Scholar 

  31. Rhetorical structure theory: description and construction of text structures. Decision Support Syst. 3(4), 360 (1987). https://doi.org/10.1016/0167-9236(87)90127-8

  32. Yang, P., Tang, K., Yao, X.: Turning high-dimensional optimization into computationally expensive optimization. IEEE Trans. Evol. Comput. 22, 143–15622 (2017)

    Article  Google Scholar 

  33. Abeysiriwardana, P.C., Kodituwakku, S.R.: Ontology based information extraction for disease intelligence. Int. J. Res. Comput. Sci. 2(6), 7–19 (2012). https://doi.org/10.7815/ijorcs.26.2012.051

    Article  Google Scholar 

  34. SWI-Prolog (1987). http://www.swi-prolog.org/

  35. SimpleNLG | DialPort (2019). http://dialport.ict.usc.edu/index.php/simplenlg/

  36. Waite, W.: Beyond LEX and YACC: How to Generate the Whole Compiler (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University Malaysia Terengganu, Kuala Terengganu, Malaysia

    Kaneeka Vidanagea, Noor Maizura Mohamad Noora, Rosmayati Mohemada & Zuriana Abu Bakara

Authors
  1. Kaneeka Vidanagea
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Noor Maizura Mohamad Noora
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rosmayati Mohemada
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zuriana Abu Bakara
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Kaneeka Vidanagea or Noor Maizura Mohamad Noora .

Editor information

Editors and Affiliations

  1. Princess Nourah Bint Abdul Rahman University, Riyadh, Saudi Arabia

    Auhood Alfaries

  2. Princess Nourah Bint Abdul Rahman University, Riyadh, Saudi Arabia

    Hanan Mengash

  3. Hasselt University, Hasselt, Belgium

    Ansar Yasar

  4. Acadia University, Wolfville, NS, Canada

    Elhadi Shakshuki

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Vidanagea, K., Noora, N.M.M., Mohemada, R., Bakara, Z.A. (2019). Domain and Schema Independent Ontology Verbalizing. In: Alfaries, A., Mengash, H., Yasar, A., Shakshuki, E. (eds) Advances in Data Science, Cyber Security and IT Applications. ICC 2019. Communications in Computer and Information Science, vol 1098. Springer, Cham. https://doi.org/10.1007/978-3-030-36368-0_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-36368-0_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36367-3

  • Online ISBN: 978-3-030-36368-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation