Abstract
Word sense disambiguation (WSD) methods evolve towards exploring all of the available semantic information that word thesauri provide. In this scope, the use of semantic graphs and new measures of semantic relatedness may offer better WSD solutions. In this paper we propose a new measure of semantic relatedness between any pair of terms for the English language, using WordNet as our knowledge base. Furthermore, we introduce a new WSD method based on the proposed measure. Experimental evaluation of the proposed method in benchmark data shows that our method matches or surpasses state of the art results. Moreover, we evaluate the proposed measure of semantic relatedness in pairs of terms ranked by human subjects. Results reveal that our measure of semantic relatedness produces a ranking that is more similar to the human generated one, compared to rankings generated by other related measures of semantic relatedness proposed in the past.
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References
Agirre, E., Edmonds, P.: Word Sense Disambiguation: Algorithms and Applications. Springer, Heidelberg (2006)
Fellbaum, C.: WordNet, An Electronic Lexical Database. MIT Press, Cambridge (1998)
Palmer, M., Fellbaum, C., Cotton, S.: English tasks: All-words and verb lexical sample. In: Proc. of Senseval-2, Toulouse, France, pp. 21–24 (2001)
Veronis, J., Ide, N.: Word sense disambiguation with very large neural networks extracted from machine readable dictionaries. In: Proc. of the 13th International Conference on Computational Linguistics, Finland, pp. 389–394 (1990)
Mihalcea, R., Tarau, P., Figa, E.: Pagerank on semantic networks with application to word sense disambiguation. In: Proc. of the 20th CoLing, Switzerland (2004)
Tsatsaronis, G., Vazirgiannis, M., Androutsopoulos, I.: Word sense disambiguation with spreading activation networks generated from thesauri. In: Proc. of the 20th International Joint Conference on Artificial Intelligence, India, pp. 1725–1730. AAAI Press, Menlo Park (2007)
Agirre, E., Rigau, G.: A proposal for word sense disambiguation using conceptual distance. In: Proc. of the 1st International Conference on Recent Advances in NLP, pp. 258–264 (1995)
Resnik, P.: Using information content to evaluate semantic similarity. In: Proc. of the 14th International Joint Conference on Artificial Intelligence, Canada, pp. 448–453 (1995)
Jiang, J., Conrath, D.: Semantic similarity based on corpus statistics and lexical taxonomy. In: Proc. of ROCLING X, Taiwan, pp. 19–33 (1997)
Hirst, G., St-Onge, D.: Lexical chains as representations of context for the detection and correction of malapropisms. In: WordNet: An Electronic Lexical Database, Ch. 13, pp. 305–332. MIT Press, Cambridge (1998)
Leacock, C., Chodorow, M.: Combining local context and wordnet similarity for word sense identification. In: WordNet: An Electronic Lexical Database, Ch. 11, pp. 265–283. MIT Press, Cambridge (1998)
Lin, D.: An information-theoretic definition of similarity. In: Proc. of the 15th International Conference on Machine Learning, pp. 296–304 (1998)
Budanitsky, A., Hirst, G.: Evaluating wordnet-based measures of lexical semantic relatedness. Computational Linguistics 32(1), 13–47 (2006)
Patwardhan, S., Banerjee, S., Pedersen, T.: Using measures of semantic relatedness for word sense disambiguation. In: Proc. of the 4th International Conference on Inbtelligent Text Processing and Computational Linguistics, pp. 241–257. Springer, Heidelberg (2003)
Mavroeidis, D., Tsatsaronis, G., Vazirgiannis, M., Theobald, M., Weikum, G.: Word sense disambiguation for exploiting hierarchical thesauri in text classification. In: Proc. of the 9th PKDD, Portugal, pp. 181–192. Springer, Heidelberg (2005)
Cowie, J., Guthrie, J., Guthrie, L.: Lexical disambiguation using simulated annealing. In: Proc. of the 14th CoLing, France, pp. 359–365 (1992)
Rubenstein, H., Goodenough, J.: Contextual correlates of synonymy. Communications of the ACM 8(10), 627–633 (1965)
Fagin, R., Kumar, R., SivaKumar, D.: Comparing top k lists. SIAM Journal on Discrete Mathematics 17(1), 134–160 (2003)
Song, Y., Han, K., Rim, H.: A term weighting method based on lexical chain for automatic summarization. In: Proc. of the 5th CICLing Conference, USA, pp. 636–639 (2004)
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Tsatsaronis, G., Varlamis, I., Vazirgiannis, M. (2008). Word Sense Disambiguation with Semantic Networks. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2008. Lecture Notes in Computer Science(), vol 5246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87391-4_29
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DOI: https://doi.org/10.1007/978-3-540-87391-4_29
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