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2017 | OriginalPaper | Buchkapitel

Unsupervised Approaches for Computing Word Similarity in Portuguese

verfasst von : Hugo Gonçalo Oliveira

Erschienen in: Progress in Artificial Intelligence

Verlag: Springer International Publishing

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Abstract

This paper presents several approaches for computing word similarity in Portuguese and is motivated by the recent availability of state-of-the-art distributional models of Portuguese words, which add to several lexical knowledge bases (LKBs) for this language, available for a longer time. The previous resources were exploited to answer word similarity tests, also recently available for Portuguese. We conclude that there are several valid approaches for this task, but not one that outperforms all the others in every single test. For instance, distributional models seem to capture relatedness better, but LKBs are better suited for computing genuine similarity.

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Vorheriges Kapitel Aspect-Based Opinion Mining in Drug Reviews
Nächstes Kapitel Gradually Improving the Computation of Semantic Textual Similarity in Portuguese
Fußnoten
4
RG-65 also targets similarity but, as far as we know, the process of differentiating similarity and relatedness was much more thorough in SimLex-999.
 
Literatur
1.
Banjade, R., Maharjan, N., Niraula, N.B., Rus, V., Gautam, D.: Lemon and tea are not similar: measuring word-to-word similarity by combining different methods. In: Gelbukh, A. (ed.) CICLing 2015. LNCS, vol. 9041, pp. 335–346. Springer, Cham (2015). doi:10.​1007/​978-3-319-18111-0_​25CrossRef
2.
Barreiro, A.: ParaMT: a paraphraser for machine translation. In: Teixeira, A., Lima, V.L.S., Oliveira, L.C., Quaresma, P. (eds.) PROPOR 2008. LNCS, vol. 5190, pp. 202–211. Springer, Heidelberg (2008). doi:10.​1007/​978-3-540-85980-2_​21CrossRef
3.
Barreiro, A.: Port4NooJ: an open source, ontology-driven Portuguese linguistic system with applications in machine translation. In: Proceedings of the 2008 International NooJ Conference (NooJ 2008). Newcastle-upon-Tyne: Cambridge Scholars Publishing, Budapest, Hungary (2010)
4.
Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information. arXiv preprint arXiv:​1607.​04606 (2016)
5.
Budanitsky, A., Hirst, G.: Evaluating wordnet-based measures of lexical semantic relatedness. Comput. Linguist. 32(1), 13–47 (2006)CrossRef
6.
Finkelstein, L., Gabrilovich, E., Matias, Y., Rivlin, E., Solan, Z., Wolfman, G., Ruppin, E.: Placing search in context: the concept revisited. ACM Trans. Inf. Syst. 20(1), 116–131 (2002)CrossRef
7.
Fonseca, E.R., dos Santos, L.B., Criscuolo, M., Aluísio, S.M.: Visão geral da avaliação de similaridade semântica e inferência textual. Linguamática 8(2), 3–13 (2016)
8.
Gonçalo Oliveira, H.: CONTO.PT: groundwork for the automatic creation of a fuzzy Portuguese wordnet. In: Silva, J., Ribeiro, R., Quaresma, P., Adami, A., Branco, A. (eds.) PROPOR 2016. LNCS, vol. 9727, pp. 283–295. Springer, Cham (2016). doi:10.​1007/​978-3-319-41552-9_​29CrossRef
9.
Gonçalo Oliveira, H.: Comparing and combining Portuguese lexical-semantic knowledge bases. In: Proceedings of the 6th Symposium on Languages, Applications and Technologies (SLATE 2017), pp. 16:1–16:14. OASICS, Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik (2017)
10.
Gonçalo Oliveira, H., Santos, D., Gomes, P., Seco, N.: PAPEL: a dictionary-based lexical ontology for Portuguese. In: Teixeira, A., Lima, V.L.S., Oliveira, L.C., Quaresma, P. (eds.) PROPOR 2008. LNCS, vol. 5190, pp. 31–40. Springer, Heidelberg (2008). doi:10.​1007/​978-3-540-85980-2_​4CrossRef
11.
Granada, R., Trojahn, C., Vieira, R.: Comparing semantic relatedness between word pairs in Portuguese using wikipedia. In: Baptista, J., Mamede, N., Candeias, S., Paraboni, I., Pardo, T.A.S., Volpe Nunes, M.G. (eds.) PROPOR 2014. LNCS, vol. 8775, pp. 170–175. Springer, Cham (2014). doi:10.​1007/​978-3-319-09761-9_​17CrossRef
12.
Harris, Z.: Distributional structure. Word 10(2–3), 146–162 (1954)CrossRef
13.
Hill, F., Reichart, R., Korhonen, A.: Simlex-999: evaluating semantic models with genuine similarity estimation. Comput. Linguist. 41(4), 665–695 (2015)MathSciNetCrossRef
14.
Lesk, M.: Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone. In: Proceedings of the 5th Annual International Conference on Systems Documentation (SIGDOC 1986), NY, USA, pp. 24–26 (1986)
15.
Luong, T., Socher, R., Manning, C.: Better word representations with recursive neural networks for morphology. In: Proceedings of the Seventeenth Conference on Computational Natural Language Learning, pp. 104–113. ACL Press, Sofia, Bulgaria, August 2013
16.
Maziero, E.G., Pardo, T.A.S., Felippo, A.D., Dias-da-Silva, B.C.: A Base de Dados Lexical e a Interface Web do TeP 2.0 - Thesaurus Eletrônico para o Português do Brasil. In: VI Workshop em Tecnologia da Informação e Linguagem Humana, pp. 390–392. TIL (2008)
17.
Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. In: Proceedings of the Workshop Track of the International Conference on Learning Representations (ICLR), Scottsdale, Arizona (2013)
18.
de Paiva, V., Rademaker, A., de Melo, G.: OpenWordNet-PT: an open brazilian wordnet for reasoning. In: Proceedings of 24th International Conference on Computational Linguistics. COLING (Demo Paper) (2012)
19.
Pilehvar, M.T., Jurgens, D., Navigli, R.: Align, disambiguate and walk: a unified approach for measuring semantic similarity. In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, ACL 2013, Sofia, Bulgaria, vol. 1: Long Papers, pp. 1341–1351. ACL Press (2013)
20.
Pilehvar, M.T., Navigli, R.: From senses to texts: an all-in-one graph-based approach for measuring semantic similarity. Artif. Intell. 228, 95–128 (2015)MathSciNetCrossRef
21.
Pinheiro, V., Furtado, V., Albuquerque, A.: Semantic textual similarity of Portuguese-language texts: an approach based on the semantic inferentialism model. In: Baptista, J., Mamede, N., Candeias, S., Paraboni, I., Pardo, T.A.S., Volpe Nunes, M.G. (eds.) PROPOR 2014. LNCS, vol. 8775, pp. 183–188. Springer, Cham (2014). doi:10.​1007/​978-3-319-09761-9_​19CrossRef
22.
Rodrigues, J., Branco, A., Neale, S., Silva, J.: LX-DSemVectors: distributional semantics models for Portuguese. In: Silva, J., Ribeiro, R., Quaresma, P., Adami, A., Branco, A. (eds.) PROPOR 2016. LNCS, vol. 9727, pp. 259–270. Springer, Cham (2016). doi:10.​1007/​978-3-319-41552-9_​27CrossRef
23.
Rubenstein, H., Goodenough, J.B.: Contextual correlates of synonymy. Commun. ACM 8(10), 627–633 (1965)CrossRef
24.
Simões, A., Sanromán, Á.I., Almeida, J.J.: Dicionário-Aberto: a source of resources for the Portuguese language processing. In: Caseli, H., Villavicencio, A., Teixeira, A., Perdigão, F. (eds.) PROPOR 2012. LNCS, vol. 7243, pp. 121–127. Springer, Heidelberg (2012). doi:10.​1007/​978-3-642-28885-2_​14CrossRef
25.
Simões, A., Guinovart, X.G.: Bootstrapping a Portuguese wordnet from galician, spanish and english wordnets. In: Navarro Mesa, J.L., Ortega, A., Teixeira, A., Hernández Pérez, E., Quintana Morales, P., Ravelo García, A., Guerra Moreno, I., Toledano, D.T. (eds.) IberSPEECH 2014. LNCS, vol. 8854, pp. 239–248. Springer, Cham (2014). doi:10.​1007/​978-3-319-13623-3_​25CrossRef
26.
Speer, R., Chin, J., Havasi, C.: Conceptnet 5.5: an open multilingual graph of general knowledge. In: Proceedings of 31st AAAI Conference on Artificial Intelligence, San Francisco, California, USA, pp. 4444–4451 (2017)
27.
28.
Turney, P.D., Pantel, P.: From frequency to meaning: vector space models of semantics. J. Artif. Intell. Res. 37(1), 141–188 (2010)MathSciNetCrossRef
29.
Wilkens, R., Zilio, L., Ferreira, E., Villavicencio, A.: B\(^2\)SG: a TOEFL-like task for Portuguese. In: Proceedings of 10th International Conference on Language Resources and Evaluation. LREC, ELRA (2016)
Metadaten
Titel
Unsupervised Approaches for Computing Word Similarity in Portuguese
verfasst von
Hugo Gonçalo Oliveira
Copyright-Jahr
2017
Buch
Progress in Artificial Intelligence

Print ISBN: 978-3-319-65339-6

Electronic ISBN: 978-3-319-65340-2

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-65340-2_67