Query refinement for ontology information extraction

Mary Ting, Abdul Kadir Rabiah, Azreen Azman, Tengku Mohd Tengku Sembok, Fatimah Dato Ahmad, Nurfadhlina Mohd Sharef

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Ontology information extraction has gain popularity due to the increasing amount of ontologies developed over the years. World Wide Web Consortium (W3C) has introduced SPARQL query language to extract information. However SPARQL query language follow a specific pattern in order to find the triple through subgraph matching. The keywords used in the SPARQL query have to be exactly same as the existing keywords in the RDF data in-order to extract the required information. The paper introduced a method to ease the job of the user by generating SPARQL query from the query entered by the user. The method uses the object property list generated from the ontology and word's synonym to aid in SPARQL query generation. The result has shown that the proposed method clearly eases the need of the user to learn SPARQL syntax.

Original languageEnglish
Title of host publication2016 3rd International Conference on Information Retrieval and Knowledge Management, CAMP 2016 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages82-87
Number of pages6
ISBN (Electronic)9781509029549
DOIs
Publication statusPublished - 4 Jan 2017
Event3rd International Conference on Information Retrieval and Knowledge Management, CAMP 2016 - Malacca, Malaysia
Duration: 23 Aug 201624 Aug 2016

Other

Other3rd International Conference on Information Retrieval and Knowledge Management, CAMP 2016
CountryMalaysia
CityMalacca
Period23/8/1624/8/16

Fingerprint

Ontology
Query languages
World Wide Web
Information extraction
Query
Key words
Query language

Keywords

  • Information Extraction
  • Ontology
  • RDF
  • SPARQL
  • Triple

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management

Cite this

Ting, M., Rabiah, A. K., Azman, A., Sembok, T. M. T., Dato Ahmad, F., & Sharef, N. M. (2017). Query refinement for ontology information extraction. In 2016 3rd International Conference on Information Retrieval and Knowledge Management, CAMP 2016 - Conference Proceedings (pp. 82-87). [7806340] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFRKM.2016.7806340

Query refinement for ontology information extraction. / Ting, Mary; Rabiah, Abdul Kadir; Azman, Azreen; Sembok, Tengku Mohd Tengku; Dato Ahmad, Fatimah; Sharef, Nurfadhlina Mohd.

2016 3rd International Conference on Information Retrieval and Knowledge Management, CAMP 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 82-87 7806340.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ting, M, Rabiah, AK, Azman, A, Sembok, TMT, Dato Ahmad, F & Sharef, NM 2017, Query refinement for ontology information extraction. in 2016 3rd International Conference on Information Retrieval and Knowledge Management, CAMP 2016 - Conference Proceedings., 7806340, Institute of Electrical and Electronics Engineers Inc., pp. 82-87, 3rd International Conference on Information Retrieval and Knowledge Management, CAMP 2016, Malacca, Malaysia, 23/8/16. https://doi.org/10.1109/INFRKM.2016.7806340
Ting M, Rabiah AK, Azman A, Sembok TMT, Dato Ahmad F, Sharef NM. Query refinement for ontology information extraction. In 2016 3rd International Conference on Information Retrieval and Knowledge Management, CAMP 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 82-87. 7806340 https://doi.org/10.1109/INFRKM.2016.7806340
Ting, Mary ; Rabiah, Abdul Kadir ; Azman, Azreen ; Sembok, Tengku Mohd Tengku ; Dato Ahmad, Fatimah ; Sharef, Nurfadhlina Mohd. / Query refinement for ontology information extraction. 2016 3rd International Conference on Information Retrieval and Knowledge Management, CAMP 2016 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 82-87
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