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MalayIK: An Ontological Approach to Knowledge Transformation in Malay Unstructured Documents

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 8 No. 1 (2018)

DOI
10.11591/ijece.v8i1.pp1-10
ISSN
2088-8708, 2088-8708
Published
2018-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

The number of unstructured documents written in Malay language is enormously available on the web and intranets. However, unstructured documents cannot be queried in simple ways, hence the knowledge contained in such documents can neither be used by automatic systems nor could be understood easily and clearly by humans. This paper proposes a new approach to transform extracted knowledge in Malay unstructured document using ontology by identifying, organizing, and structuring the documents into an interrogative structured form. A Malay knowledge base, the MalayIK corpus is developed and used to test the MalayIK-Ontology against Ontos, an existing data extraction engine. The experimental results from MalayIK-Ontology have shown a significant improvement of knowledge extraction over Ontos implementation. This shows that clear knowledge organization and structuring concept is able to increase understanding, which leads to potential increase in sharable and reusable of concepts among the community.

Collaboration network of the authors

7 authors · 13 co-authorship links · 4 across different organisations

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  • Universiti Putra Malaysia
  • Universiti Sains Islam Malaysia
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Khairi Azhar AzizUniversiti Putra Malaysia1
Salfarina AbdullahUniversiti Putra Malaysia1
Rozi Nor Haizan NorUniversiti Putra Malaysia1
Nur Ilyana Ismarau TajuddinUniversiti Sains Islam Malaysia1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 1 Nov 2026.
Metadata as oai_dc, converted from Crossref
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