An Intelligent and Advance Kurdish Information Retrieval Approach with Ontologies: A Critical Analysis
Keywords:Intelligent Approach, Kurdish Language, Kurdish Ontology, Search engines, Semantic Web, Ontology Development, Information retrieval, Web content
Today, there are numerous methods of finding information online: radio, TV, and the internet all provide answers. However, the Internet stands out as being particularly helpful; users can search by typing in questions related to any subject area they wish. Results appear as links to various documents available on the internet, some of which may not even be relevant due to the vast amount of material. Search engines reliant solely on keywords are incapable of making sense of raw data, making it time-consuming and costly to extract critical pieces from an immense collection of web pages. Due to these deficiencies, several concepts were born, such as the Semantic Web (SW) and ontologies. SW serves as an excellent gateway for retrieving key information through various Information Retrieval (IR) techniques. IR algorithms are too simplistic to extract the semantic content from texts. IR, SW, and ontologies can all be used interchangeably, although all three have some connection. The SW can be achieved through IR, while indexing can lead to its creation on the web. The SW is also created through ontologies. Ontologies can be used together with the intelligent approaches to produce web content, which is then marked up using SW Documents. Ontology is the backbone of any software; therefore, the SW becomes simpler to comprehend. Ontology development is the process of creating and refining an ontology over time. This paper investigates various approaches, methodologies, and datasets used to address challenges in information retrieval, including corpus preparation, annotation techniques, query expansion, semantic reasoning, content alignment, and ontology-based retrieval systems.
S. L. Tomassen, “Research on ontology-driven information retrieval,” presented at the OTM Workshops (2), 2006, pp. 1460–1468.
V. Mateljan, V. Juričić, and D. Ogrizović, “DOCUMENT SIMILARITY IN REPEATEDLY TRANSLATED CORPORA.,” Teh. Vjesn. Gaz., vol. 24, no. 2, 2017.
F. A. Allah, S. Boulaknadel, and D. Aboutajdine, “Arabic information retrieval system based on noun phrases,” presented at the 2006 2nd International Conference on Information & Communication Technologies, IEEE, 2006, pp. 1720–1725.
R. Kumar and S. Sharma, “Information retrieval system: An overview, issues, and challenges,” Int. J. Technol. Diffus. IJTD, vol. 9, no. 1, Art. no. 1, 2018.
Z. Dan, “Research on Semantic Information Retrieval Based on Ontology,” presented at the Proceedings of the 7th International Conference on Innovation & Management, Page, 2011.
M. A. Raza, R. Mokhtar, N. Ahmad, M. Pasha, and U. Pasha, “A taxonomy and survey of semantic approaches for query expansion,” IEEE Access, vol. 7, pp. 17823–17833, 2019.
K. Jacksi, N. Dimililer, and S. R. Zeebaree, “A survey of exploratory search systems based on LOD resources,” 2015.
A. Allot, Y. Peng, C.-H. Wei, K. Lee, L. Phan, and Z. Lu, “LitVar: a semantic search engine for linking genomic variant data in PubMed and PMC,” Nucleic Acids Res., vol. 46, no. W1, Art. no. W1, 2018.
W. Dan and W. Hui-Lin, “Role of ontology in information retrieval,” J. Electron. Sci. Technol., vol. 4, no. 2, Art. no. 2, 2006.
B. Yu, “Research on information retrieval model based on ontology,” EURASIP J. Wirel. Commun. Netw., vol. 2019, no. 1, Art. no. 1, 2019.
D. Sullivan, “Death of a meta tag,” Search Engine Watch, vol. 1, 2002.
S. Jun-feng, Z. Wei-ming, X. Wei-dong, L. Guo-hui, and X. Zhen-ning, “Ontology-based information retrieval model for the semantic web,” presented at the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service, IEEE, 2005, pp. 152–155.
S. H. Haji, K. Jacksi, and R. M. Salah, “Systematic Review for Selecting Methods of Document Clustering on Semantic Similarity of Online Laboratories Repository,” presented at the The International Conference on Innovations in Computing Research, Springer, 2022, pp. 239–252.
K. J. A Zeebaree SRM Zeebaree, “Designing an Ontology of E-learning system for Duhok Polytechnic University Using Protégé OWL Tool,” J Adv Res Dyn Control Syst Vol, vol. 11, no. 5, pp. 24–37, 2019.
R. M. Braga, C. M. L. Werner, and M. Mattoso, “Using ontologies for domain information retrieval,” presented at the Proceedings 11th International Workshop on Database and Expert Systems Applications, IEEE, 2000, pp. 836–840.
K. Jacksi, S. R. Zeebaree, and N. Dimililer, “LOD Explorer: Presenting the Web of Data,” Int. J. Adv. Comput. Sci. Appl., vol. 9, no. 1, Art. no. 1, 2018.
D. Maulud, K. Jacksi, and I. Ali, “Towards a Complete Kurdish NLP Pipeline: Challenges and Opportunities,” J. Inform., vol. 17, no. 1, pp. 1–17, 2023.
K. Jacksi and I. Ali, “The Kurdish Language corpus: state of the art,” Sci. J. Univ. Zakho, vol. 11, no. 1, pp. 127–133, 2023.
M. Gökırmak and F. Tyers, “A dependency treebank for Kurmanji Kurdish,” presented at the Proceedings of the Fourth International Conference on Dependency Linguistics (Depling 2017), 2017, pp. 64–72.
D. Ataman, “Bianet: A parallel news corpus in Turkish, Kurdish and English,” ArXiv Prepr. ArXiv180505095, 2018.
J. J. Carroll, I. Dickinson, C. Dollin, D. Reynolds, A. Seaborne, and K. Wilkinson, “Jena: implementing the semantic web recommendations,” presented at the Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters, 2004, pp. 74–83.
J. Paralic and I. Kostial, “Ontology-based information retrieval,” presented at the Proceedings of the 14th International Conference on Information and Intelligent systems (IIS 2003), Varazdin, Croatia, Citeseer, 2003, pp. 23–28.
S. R. M. Z. Adel AL-Zebari Karwan Jacksi and Ali Selamat, “ELMS–DPU Ontology Visualization with Protégé VOWL and Web VOWL,” J. Adv. Res. Dyn. Control Syst., vol. 11, no. 1, pp. 478–485, 2019.
G. Singh and V. Jain, “Information retrieval (IR) through semantic web (SW): an overview,” ArXiv Prepr. ArXiv14037162, 2014.
I. Szilagyi and P. Wira, “Ontologies and Semantic Web for the Internet of Things-a survey,” presented at the IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society, IEEE, 2016, pp. 6949–6954.
S. Ahmadi, H. Hassani, and J. P. McCrae, “Towards electronic lexicography for the Kurdish language,” presented at the Proceedings of the sixth biennial conference on electronic lexicography (eLex), eLex 2019, 2019.
S. Ahmadi, H. Hassani, and D. Q. Jaff, “Leveraging Multilingual News Websites for Building a Kurdish Parallel Corpus,” Trans. Asian Low-Resour. Lang. Inf. Process., vol. 21, no. 5, Art. no. 5, 2022.
S. Jain, K. Seeja, and R. Jindal, “A fuzzy ontology framework in information retrieval using semantic query expansion,” Int. J. Inf. Manag. Data Insights, vol. 1, no. 1, Art. no. 1, 2021.
V. F. Salgado, D. B. de Lima Santos, F. G. de Carvalho Dutra, F. S. Parreiras, and W. C. Brandão, “Ontology-based Approach for Business Opportunities Recognition.,” presented at the ICEIS (1), 2021, pp. 594–601.
M. Tang, J. Chen, and H. Chen, “SemOIR: an ontology-based semantic information retrieval system,” presented at the 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C), IEEE, 2020, pp. 204–208.
N. M. Shati, N. khalid Ibrahim, and T. M. Hasan, “A review of image retrieval based on ontology model,” J. Al-Qadisiyah Comput. Sci. Math., vol. 12, no. 1, Art. no. 1, 2020.
N. Rastogi, P. Verma, and P. Kumar, “Evaluation of information retrieval performance metrics using real estate ontology,” presented at the 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), IEEE, 2020, pp. 102–106.
G. Ren, H. Li, S. Liu, J. Goonetillake, A. Khudhair, and S. Arthur, “Aligning BIM and ontology for information retrieve and reasoning in value for money assessment,” Autom. Constr., vol. 124, p. 103565, 2021.
N. S. Ekene, O. E. Moibi, and A. B. Abaioni, “Restaurant Multi-Context-Based Information Retrieval System Ontological Model,” Covenant J. Inform. Commun. Technol., 2021.
R. Kumar and S. Sharma, “Smart Information Retrieval using Query Transformation based on Ontology and Semantic-Association,” Int. J. Adv. Comput. Sci. Appl., vol. 13, no. 4, Art. no. 4, 2022.
A. Zidi and M. Abed, “A generalized framework for ontology-based information retrieval: Application to a public-transportation system,” presented at the 2013 International Conference on Advanced Logistics and Transport, IEEE, 2013, pp. 165–169.
K. Jacksi, N. Dimililer, and S. Zeebaree, “State of the art exploration systems for linked data: a review,” Int J Adv Comput Sci Appl IJACSA, vol. 7, no. 11, pp. 155–164, 2016.
G. Lan, T. Liu, X. Wang, X. Pan, and Z. Huang, “A semantic web technology index,” Sci. Rep., vol. 12, no. 1, Art. no. 1, 2022.
P. Sorg, “Exploiting social semantics for multilingual information retrieval,” 2011.
T. Berners-Lee et al., “34 The Semantic Web,” 2001.
A.-Z. Adel, S. Zebari, and K. Jacksi, “Football Ontology Construction using Oriented Programming,” J. Appl. Sci. Technol. Trends, vol. 1, no. 1, pp. 24–30, 2020.
U. de N. IRIN, “Indexing a Web Site with a Terminology Oriented Ontology”.
M. Q. Shatnawi, M. B. Yassein, and R. Mahafza, “A framework for retrieving Arabic documents based on queries written in Arabic slang language,” J. Inf. Sci., vol. 38, no. 4, Art. no. 4, 2012.
K. Jacksi, “Design and Implementation of E-Campus Ontology with a Hybrid Software Engineering Methodology,” Sci. J. Univ. Zakho, vol. 7, no. 3, pp. 95–100, 2019.
R. Blanco González, “Index compression for information retrielval systems,” 2008.
K. Jacksi and S. Badiozamany, “General method for data indexing using clustering methods,” Int J Sci Eng, vol. 6, no. 3, pp. 641–644, 2015.
K. Jacksi and N. Salih, “State of the art document clustering algorithms based on semantic similarity,” J. Inform., vol. 14, no. 2, Art. no. 2, May 2020, doi: 10.26555/jifo.v14i2.a17513.
S. R. Z. Karwan Jacksi Nazife Dimililer, “AN IMPROVED APPROACH FOR INFORMATION RETRIEVAL WITH SEMANTIC-WEB CRAWLING,” University of Zakho, 2018.
Rose, J. D. ., R, V. R. ., Lakshmi, D., Saranya, S. ., & Mohanaprakash, T. A. . (2023). Privacy Preserving and Time Series Analysis of Medical Dataset using Deep Feature Selection. International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 51–57. https://doi.org/10.17762/ijritcc.v11i3.6201
Hiroshi Yamamoto, An Ensemble Learning Approach for Credit Risk Assessment in Banking , Machine Learning Applications Conference Proceedings, Vol 1 2021.
Sherje, N. P., Agrawal, S. A., Umbarkar, A. M., Dharme, A. M., & Dhabliya, D. (2021). Experimental evaluation of mechatronics based cushioning performance in hydraulic cylinder.Materials Today: Proceedings, doi:10.1016/j.matpr.2020.12.1021
How to Cite
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.