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Enhancing Wordnet against Overlapping Returns of Senses for Efficient Polysemy Representation in Ontology Development

Enesi Femi Aminu*, Qasim Adewale Fajobi**, Ishaq Oyebisi Oyefolahan***, Muhammad Bashir Abdullahi****, Muhammadu Tajudeen Salaudeen*****

* Lecturer, Department of Computer Science, Federal University of Technology, Minna, Nigeria.

** Department of Computer Science, Federal University of Technology, Minna, Nigeria.

*** Senior Lecturer, Department of Information and Media Technology, Federal University of Technology, Minna, Nigeria.

**** Head, Department of Computer Science, Federal University of Technology, Minna, Nigeria.

***** Senior Lecturer and Head, Department of Crop Production, Federal University of Technology, Minna, Nigeria.

Periodicity:March - May'2019
DOI : https://doi.org/10.26634/jcom.7.1.15720

Abstract

In order to have a web of relevant information retrieval otherwise, known as semantic web, ontology has been identified as its core stronghold to actualize the dream. Ontology is a data modeling or knowledge representation technique for structured data repository premised on collection of concepts with their semantic relationships and constraints on particular area of knowledge. Example is wordNet which is linguistic based and popular ontology which has been greatly used to be part of ontology based information retrieval system development. However, the existing wordNet would affect the expected accurate results of such system owing to its overlapping return of senses. Therefore, this research aimed to design algorithm with the aid of extended Levenshtein similarity matching function and WordWeb to proffer solution to the militating problem. At the end, an enhanced wordNet that devoid of overlapping returns of senses for efficient polysemy representation in terms of user's time and system's memory would be achieved.

Keywords

Semantic web, Ontology, WordNet, WordWeb, Senses, Polysemy and Levenshtein

How to Cite this Article?

Aminu,E.F., Fajobi,Q.A., Oyefolahan,I.O., Abdullahi,M.B., Salaudeen,M.T.(2019) Enhancing WordNet Against Overlapping Returns of Senses for Efficient Polysemy Representation in Ontology Development, i-manager's Journal on Computer Science, 7(1), 17-24. https://doi.org/10.26634/jcom.7.1.15720

References

[1]. Al-Yahya, M., George, R., & Alfaries, A. (2015). Ontologies in E-learning: Review of the literature. International Journal of Software Engineering and Its Applications, 9(2), 67-84.

[2]. Barque, L., & Chaumartin, F. R. (2009). Regular polysemy in WordNet. JLCL-Journal for Language Technology and Computational Linguistics, 24(2), 5-18.

[3]. Basile, V. (2015). WordNet as an Ontology for Generation. WebNLG 2015 1^st International Workshop on Natural Language Generation from the Semantic Web.

[4]. Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific American, 284(5), 34-43.

[5]. Boleda, G., Walde, S. S, I., & Badia, T. (2012). Modeling regular polysemy: A study on the semantic classification of catalan adjectives. Computational Linguistics, 38(3), 575-616.

[6]. Carpineto, C., & Romano, G. (2012). A survey of automatic query expansion in information retrieval. ACM Computing Surveys (CSUR), 44(1), 1-38.

[7]. Devi, M. U., & Gandhi. G. M. (2015). WordNet and Ontology based Quer y Expansion for Semantic Information Retrieval in sports domain. Journal of Computer Science, 11(2), 361-371.

[8]. Fensel, D., Van Harmelen, F., Horrocks, I., McGuinness, D. L., & Patel-Schneider, P. F. (2001). OIL: An ontology infrastructure for the semantic web. IEEE Intelligent Systems, 16(2), 38-45.

[9]. Freeman, A. T., Condon, S. L., & Ackerman, C. M. (2006, June). Cross linguistic name matching in English and Arabic: A one to many mapping extension of the Levenshtein edit distance algorithm. In Proceedings of the Main Conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics (pp. 471-478). Association for Computational Linguistics.

[10]. Freihat, A. A., Dutta, B., & Giunchiglia, F. (2015). Compound noun polysemy and sense enumeration in wordnet. In Proceedings of the 7^th International Conference on Information, Process, and Knowledge Management (eKNOW) (pp. 166-171).

[11]. Freihat, A. A., Giunchiglia, F., & Dutta, B. (2016, January). A taxonomic classification of wordnet polysemy types. In Global WordNet Conference (p. 105).

[12]. Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2), 199-220.

[13]. Jiamjitvanich, K. & Yatskevich, M. (n.d). Reducing polysemy in WordNet. Department of Information and Communication Technology, University of Trento, Italy.

[14]. Jiamjitvanich, K., & Yatskevich, M. (2008). Reducing polysemy in WordNet. University of Trento.

[15]. Laparra, E., & Rigau, G. (2009). Integrating WordNet and framenet using a knowledge-based word sense disambiguation algorithm. In Proceedings of the International Conference RANLP-2009 (pp. 208-213).

[16]. Laparra, E., Rigau, G., & Cuadros, M. (2010, February). Exploring the integration of WordNet and FrameNet. In Proceedings of the 5^thGlobal WordNet Conference (GWC 2010).

[17]. Lutz, M., & Klien, E. (2006). Ontology based retrieval of geographic information. International Journal of Geographical Information Science, 20(3), 233-260.

[18]. Nandini, D. (2014). Semantic Web and Ontology (eBooks and textbooks from bookboon. com). Retrieved from https://bookboon.com/en/semantic-web-and-ontology- ebook

[19]. Rodríguez-García, M. Á., Valencia-García, R., García-Sánchez, F., & Samper-Zapater, J. J. (2014). Ontology-based annotation and retrieval of services in the cloud. Knowledge-Based Systems, 56, 15-25.

[20]. Sánchez, D., Isern, D., & Millan, M. (2011). Content annotation for the semantic web: an automatic web-based approach. Knowledge and Information Systems, 27(3), 393-418.

[21]. Singh, J., & Sharan, A. (2017). A new fuzzy logic-based query expansion model for efficient information retrieval using relevance feedback approach. Neural Computing and Applications, 28(9), 2557-2580.

[22]. Singla, N., & Garg, D. (2012). String matching algorithms and their applicability in various applications. International Journal of Soft Computing and Engineering, 1(6), 218-222.

[23]. Uthayan, K. R., & Anandha Mala, G. S. (2015). Hybrid ontology for semantic information retrieval model using keyword matching indexing system. The Scientific World Journal, 2015.

[24]. Vijayarajan, V., Dinakaran, M., Tejaswin, P., & Lohani, M. (2016). A generic framework for ontology-based information retrieval and image retrieval in web data. Human-centric Computing and Information Sciences, 6(1), 18.

[25]. Wache, H., Voegele, T., Visser, U., Stuckenschmidt, H., Schuster, G., Neumann, H., & Hübner, S. (2001, August). Ontology-based integration of information-a survey of existing approaches. In IJCAI-01 Workshop: Ontologies and Information Sharing (Vol. 2001, pp. 108- 117).

[26]. Wei, Y. Y., Wang, R. J., Hu, Y. M., & Xue, W. (2012). From web resources to agricultural ontology: A method for semi-automatic construction. Journal of Integrative Agriculture, 11(5), 775-783.

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Enhancing Wordnet against Overlapping Returns of Senses for Efficient Polysemy Representation in Ontology Development

Abstract

Keywords

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References

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