A Hybrid Approach to Ontology Construction for the Badini Kurdish Language

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3ABL6LLMCQ" target="_blank" >RIV/00216208:11320/25:BL6LLMCQ - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205272486&doi=10.3390%2finfo15090578&partnerID=40&md5=a7dde8f16438402eddab39add53099a4" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205272486&doi=10.3390%2finfo15090578&partnerID=40&md5=a7dde8f16438402eddab39add53099a4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/info15090578" target="_blank" >10.3390/info15090578</a>

Result language

angličtina

Original language name

A Hybrid Approach to Ontology Construction for the Badini Kurdish Language

Original language description

Semantic ontologies have been widely utilized as crucial tools within natural language processing, underpinning applications such as knowledge extraction, question answering, machine translation, text comprehension, information retrieval, and text summarization. While the Kurdish language, a low-resource language, has been the subject of some ontological research in other dialects, a semantic web ontology for the Badini dialect remains conspicuously absent. This paper addresses this gap by presenting a methodology for constructing and utilizing a semantic web ontology for the Badini dialect of the Kurdish language. A Badini annotated corpus (UOZBDN) was created and manually annotated with part-of-speech (POS) tags. Subsequently, an HMM-based POS tagger model was developed using the UOZBDN corpus and applied to annotate additional text for ontology extraction. Ontology extraction was performed by employing predefined rules to identify nouns and verbs from the model-annotated corpus and subsequently forming semantic predicates. Robust methodologies were adopted for ontology development, resulting in a high degree of precision. The POS tagging model attained an accuracy of 95.04% when applied to the UOZBDN corpus. Furthermore, a manual evaluation conducted by Badini Kurdish language experts yielded a 97.42% accuracy rate for the extracted ontology. © 2024 by the authors.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Information (Switzerland)

ISSN

2078-2489

e-ISSN

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Volume of the periodical

15

Issue of the periodical within the volume

9

Country of publishing house

US - UNITED STATES

Number of pages

19

Pages from-to

1-19

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85205272486