Abstract
In this paper, we propose to complement the context vectors used in bilingual lexicon extraction from comparable corpora with concept vectors, that aim at capturing all the words related to the concepts associated with a given word. This allows one to rely on a representation that is less sparse, especially in specialized domains where the use of a general bilingual lexicon leaves many words untranslated. The concept vectors we are considering are based on closed concepts mining developed in Formal Concept Analysis (FCA). The obtained results on two different comparable corpora show that enriching context vectors with concept vectors leads to lexicons of higher quality, especially in specialized domains.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
A parallel corpus is a collection of texts that are translation of one another.
- 2.
A comparable corpus is a collection of multilingual documents dealing with the same topics and generally produced at the same time. They are not necessarily translation of each other.
- 3.
- 4.
One can also translate each element of the source context vectors into the target language.
- 5.
In this paper, we denote by |X| the cardinality of the set X.
- 6.
- 7.
- 8.
References
Andrade, D., Matsuzaki, T., Tsujii, J: Effective use of dependency structure for bilingual Lexicon creation. In: Gelbukh, A. (ed.) CICLing 2011. LNCS, vol. 6609, pp. 80–92. Springer, Heidelberg (2011). doi:10.1007/978-3-642-19437-5_7
Barker, K., Cornacchia, N.: Using noun phrase heads to extract document keyphrases. In: Hamilton, H.J. (ed.) AI 2000. LNCS (LNAI), vol. 1822, pp. 40–52. Springer, Heidelberg (2000). doi:10.1007/3-540-45486-1_4
Chebel, M., Latiri, C., Gaussier, E.: Extraction of interlingual documents clusters based on closed concepts mining. In: 19th International Conference KES 2015, Singapore, pp. 537–546 (2015)
Fung, P.: A statistical view on bilingual Lexicon extraction: from parallel corpora to non-parallel corpora. In: Farwell, D., Gerber, L., Hovy, E. (eds.) AMTA 1998. LNCS (LNAI), vol. 1529, pp. 1–17. Springer, Heidelberg (1998). doi:10.1007/3-540-49478-2_1
Ganter, B., Wille, R.: Formal Concept Analysis. Springer, Heidelberg (1999)
Baroni, M., Georgiana, D., Kruszewski, G.: Don’t count, predict! a systematic comparison of context-counting vs. context-predicting semantic vectors. In: 52nd Annual Meeting ACL 2014, Baltimore, Maryland (2014)
Laroche, A., Langlais, P.: Revisiting context-based projection methods for term-translation spotting in comparable corpora. In: 23rd International Conference COLING 2010, Beijing, China, pp. 617–625 (2010)
Li, B., Gaussier, E.: An information-based cross-language information retrieval model. In: Baeza-Yates, R., Vries, A.P., Zaragoza, H., Cambazoglu, B.B., Murdock, V., Lempel, R., Silvestri, F. (eds.) ECIR 2012. LNCS, vol. 7224, pp. 281–292. Springer, Heidelberg (2012). doi:10.1007/978-3-642-28997-2_24
Linard, A., Daille, B., Emmanuel, M.: Attempting to bypass alignment from comparable corpora via pivot language. In: 8th Workshop on BUCC, Beijing, pp. 32–37 (2015)
Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008)
Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: NIPS, vol. 2013, pp. 3111–3119 (2013)
Morin, E., Hazem, A.: Looking at unbalanced specialized comparable corpora for bilingual Lexicon extraction. In: ACL 2014, Baltimore, USA, pp. 284–293 (2014)
Gamallo Otero, P.: Comparing window and syntax based strategies for semantic extraction. In: Teixeira, A., Lima, V.L.S., Oliveira, L.C., Quaresma, P. (eds.) PROPOR 2008. LNCS (LNAI), vol. 5190, pp. 41–50. Springer, Heidelberg (2008). doi:10.1007/978-3-540-85980-2_5
Pasquier, N., Taouil, R., Bastide, Y., Stumme, G., Lakhal, L.: Generating a condensed representation for association rules. J. Intell. Inf. Syst. 2005, 29–60 (2005)
Prochasson, E., Morin, E.l., Kageura, K.: Anchor points for bilingual Lexicon extraction from small comparable corpora. In: Machine Translation Summit, France (2009)
Ronan, C., Jason, W.: A unified architecture for natural language processing: deep neural networks with multitask learning. In: ICML2008, pp. 160–167 (2008)
Salton, G., Buckley, C.: Term-weighting Approaches in Automatic Text Retrieval. Information Processing Management. Pergamon Press Inc, Tarrytown (1988)
Zaki, M.J., Hsiao, C.J.: Efficient algorithms for mining closed itemsets and their lattice structure. IEEE Trans. Knowl. Data Eng. 17, 462–478 (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Chebel, M., Latiri, C., Gaussier, E. (2017). Bilingual Lexicon Extraction from Comparable Corpora Based on Closed Concepts Mining. In: Kim, J., Shim, K., Cao, L., Lee, JG., Lin, X., Moon, YS. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2017. Lecture Notes in Computer Science(), vol 10234. Springer, Cham. https://doi.org/10.1007/978-3-319-57454-7_46
Download citation
DOI: https://doi.org/10.1007/978-3-319-57454-7_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-57453-0
Online ISBN: 978-3-319-57454-7
eBook Packages: Computer ScienceComputer Science (R0)