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Hybrid Method for Semantic Similarity Computation Using Weighted Components in Ontology

Published: 07 October 2022 Publication History

Abstract

In this paper, the researchers propose an approach to measure the semantic similarity between two concepts in an ontology like WordNet and DBpedia. Some earlier semantic similarity approaches proposed concentrated on the ontology structure between concepts and some concentrated only on the information content of concepts. This paper proposes a semantic similarity approach with path length, information content, and semantic depth (i.e., PLICD) to combine both path length as well as information content-based approaches. This proposed approach uses weighted shortest path length and information content calculated using semantic depth and hyponyms of the concepts to measure semantic similarity between two concepts. Through experimentations performed on WordNet and DBpedia, the researchers note that the PLICD semantic similarity approach has delivered a statistically meaningful enhancement as compared to the other semantic similarity approaches concerning accuracy and F score.

References

[1]
BanerjeeS.PedersenT. (2003). Extended gloss overlaps as a measure of semantic relatedness. Proceedings of the International Joint Conference on Artificial Intelligence, 3, 805–810.
[2]
Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., & Hellmann, S. (2009). Dbpedia-a crystallization point for the web of data . Web Semantics: Sci. Services Agents World Wide Web, 7(3), 154–165.
[3]
Bojanowski, P., Grave, E., Joulin, A., & Mikolov, T. (2017). Enriching word vectors with subword information. Transactions of the Association for Computational Linguistics, 5, 135–146.
[4]
Gao, J.-B., Zhang, B.-W., & Chen, X.-H. (2015). A WordNet-based semantic similarity measurement combining edge-counting and information content theory. Engineering Applications of Artificial Intelligence, 39, 80–88.
[5]
GormanJ.CurranJ. R. (2006). Scaling distributional similarity to large corpora. Proceedings of the 21st International Conference on Computational Linguistics and 44th Meeting of the Association for Computational Linguistics, 361–368.
[6]
Jiang, Y., Zhang, X., Tang, Y., & Nie, R. (2015). Feature-based approaches to semantic similarity assessment of concepts using Wikipedia. Information Processing & Management, 51(3), 215–234.
[7]
Landauer & Dumais. (1997). A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychol. Rev., 104(2), 211.
[8]
LeWangQuanHeYao. (2018). ACV-tree: A new method for sentence similarity modeling. Proceedings of the International Joint Conference on Artificial Intelligence, 4137–4143. 10.24963/ijcai.2018/575
[9]
Leacock & Chodorow. (1998). Combining local context and WordNet similarity for word sense identification. WordNet: An Electronic Lexical Database, 49(2), 265-283.
[10]
Li, Y., Bandar, Z., & Mclean, D. (2003, July/August). An approach for measuring semantic similarity between words using multiple information sources . IEEE Transactions on Knowledge and Data Engineering, 15(4), 871–882.
[11]
LinD. (1998). An information-theoretic definition of similarity. Proc.15th Int. Conf. Machine Learn., 296–304.
[12]
Lund, K., & Burgess, C. (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments, & Computers, 28(2), 203–208.
[13]
Meng, L., Gu, J., & Zhou, Z. (2012). A new model of information content based on concept’s topology for measuring semantic similarity in WordNet. International Journal of Grid and Distributed Computing, 5(3), 81–94.
[14]
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. Arxiv Preprint Arxiv:1301.3781.
[15]
Miller, A. (1995). WordNet: A lexical database for english . Communications of the ACM, 38(11), 39–41.
[16]
PenningtonJ.SocherR.ManningC. D. (2014). GloVe: Global vectors for word representation. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP’14), 1532–1543.
[17]
Rada, R., Mili, H., Bicknell, E., & Blettner, M. (1989, January-February). Development and application of a metric on semantic nets . IEEE Transactions on Systems, Man, and Cybernetics, 19(1), 17–30.
[18]
ResnikP. (1995). Using information content to evaluate semantic similarity in a taxonomy. Proc. 14th Int. Joint Conf. Artif. Intell., 448–453.
[19]
Sánchez, D., Batet, M., Isern, D., & Valls, A. (2012). Ontology-based semantic similarity: A new feature-based approach. Expert Systems with Applications, 39(9), 7718–7728.
[20]
WuZ.PalmerM. (1994). Verbs semantics and lexical selection. Proc. 32nd Annu. Meeting Assoc. Comput. Linguistics, 133– 138. 10.3115/981732.981751
[21]
Zhu, G., & Iglesias, C. A. (2017, January). Computing semantic similarity of concepts in knowledge graphs. IEEE Transactions on Knowledge and Data Engineering, 29(1), 72–85.

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            Published In

            cover image International Journal of Software Innovation
            International Journal of Software Innovation  Volume 10, Issue 1
            Sep 2022
            2247 pages
            ISSN:2166-7160
            EISSN:2166-7179
            Issue’s Table of Contents

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            IGI Global

            United States

            Publication History

            Published: 07 October 2022

            Author Tags

            1. DBpedia
            2. Information Content
            3. Knowledge-Based Methods
            4. Ontology
            5. PLICD
            6. Semantic Similarity
            7. Weighted Shortest Path
            8. WordNet

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