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Lista de candidatos sometidos a examen:
1) sense disambiguation (*)
(*) Términos presentes en el nuestro glosario de lingüística
1) Candidate: sense disambiguation
Is in goldstandard
1
paper corpusSignostxt336 - : Before formulating the linguistic point we are going to test via computer experiments, we will first localize it within the vast realm of linguistics. Our statement is concerned with the concept of collocation, one of contemporary controversial issues in theoretical and applied linguistics. Knowledge of collocation is very important in lexicology (Herbst & Mittmann, 2008), translation (Boonyasaquan, 2006), language acquisition (Handl, 2008), and in various tasks of automated processing of natural language (e.g., in automatic word sense disambiguation: Jin, Sun, Wu & Yu, 2007 ; in machine translation: Wehrli, Seretan, Nerima & Russo, 2009; in text classification: Williams, 2002, etc.).
Evaluando al candidato sense disambiguation:
sense disambiguation
Lengua:
Frec: 67
Docs: 8
Nombre propio: / 67 = 0%
Coocurrencias con glosario:
Puntaje: 0.141 = ( + (1+0) / (1+6.08746284125034)));
Candidato aceptado
Referencias bibliográficas encontradas sobre cada término
(Que existan referencias dedicadas a un término es también indicio de terminologicidad.)| sense disambiguation |
: Agirre, A. y Edmonds, Ph. (Eds.). 2007. Word sense disambiguation algorithms and applications. Text, Speech and Language Technology, Vol. 33. Berlin, Heidelberg, New York: Springer-Verlag. : Agirre, E., de Lacalle, O. L. & Soroa, A. (2014). Random walks for knowledge-based word sense disambiguation. Computational Linguistics, 40(1), 57-84. : Ando, R. K. (2006). Applying alternating structure optimization to word sense disambiguation. Proceedings of the Tenth Conference on Computational Natural Language Learning (pp. 77-84). Association for Computational Linguistics. : Banerjee, S. & Pedersen, T. (2002). An adapted lesk algorithm for word sense disambiguation using wordnet. Proceedings of the CICLing 2002 Conference (pp. 136-145). LNCS: Springer-Verlag. : Basile, P., Caputo, A. & Semeraro, G. (2014). An enhanced lesk word sense disambiguation algorithm through a distributional semantic model. Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers (pp. 1591-1600). : Borah, P. P., Talukdar, G. & Baruah, A. (2014). Approaches for word sense disambiguation -A survey. International Journal of Recent Technology and Engineering, 3(1), 35-38. : Carpuat, M. & Wu, D. (2007). Improving statistical machine translation using word sense disambiguation. Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learnin (pp. 61-72). : Chan, Y. S., Ng, H. T. & Chiang, D. (2007). Word sense disambiguation improves statistical machine translation. Annual Meeting-Association for Computational Linguistics, 45(1), 33. : Chaplot, D. S., Bhattacharyya, P. & Paranjape, A. (2015). Unsupervised word sense disambiguation using markov random field and dependency parser. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (pp. 2217-2223). : Ciaramita, M. & Altun, Y. (2006). Broad-coverage sense disambiguation and information extraction with a supersense sequence tagger. Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (pp. 594-602). Association for Computational Linguistics. : Cottrell, G. W. (1989). A connectionist approach to word sense disambiguation. Pitman: London, U.K. : Escudero, G., Márquez, L. & Rigau, G. (2000). Naive Bayes and exemplar-based approaches to word sense disambiguation revisited. Proceedings of the 14th European Conference on Artificial Intelligence (ECAI) (pp. 421-425), Berlin, Germany. : Gliozzo, A., Giuliano, C. & Strapparava, C. (2005a). Domain kernels for word sense disambiguation. Proceedings of ACL, Michigan, U.S.A. : Gliozzo, A., Magnini, B. & Strapparava, C. (2004). Unsupervised domain relevance estimation for word sense disambiguation. Proceedings of the Empirical Methods in Natural Language Processing Conference, Barcelona, Spain. : Huang, Z., Chen, Y. & Shi, X. (2013). A novel word sense disambiguation algorithm based on semi-supervised statistical learning. International Journal of Applied Mathematics and Statistics™, 43(13), 452-458. : Ide, N. & Véronis, J. 1998. "Word Sense Disambiguation: The State of the Art", en Computational Linguistics, 24 (1), pp. 1-41. : Jin, P., Sun, X., Wu,Y. & Yu, S. (2007). Word clustering for collocation-based word sense disambiguation. In P. Jin, X. Sun,Y.Wu & S.Yu (Eds.), Lecture notes in computer science: Computational linguistics and intelligent text processing (pp. 267–274). Berlin: Springer-Verlag. : Lesk, M. (1986). Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone. Proceedings of the 5th annual international conference on Systems documentation (pp. 24-26). ACM. : Mihalcea, R. (2004). Co-training and self-training for word sense disambiguation. Proceedings of the 8th Conference on Natural Language Learning (pp. 33-40). : Mihalcea, R. 2006. "Knowledge-Based Methods for WSD". En E. Agirre & P. Edmonds (Eds.), Word Sense Disambiguation, Algorithms and Applications Springer. pp. 127-132: : Navigli, R. & Lapata, M. (2010). An experimental study of graph connectivity for unsupervised word sense disambiguation. IEEE transactions on pattern analysis and machine intelligence, 32(4), 678-692. : Navigli, R. (2009). Word sense disambiguation: A survey. ACM Computing Surveys (CSUR), 41(2), 10. : Navigli, R. (2012). A quick tour of word sense disambiguation, induction and related approaches. International Conference on Current Trends in Theory and Practice of Computer Science (pp. 115-129). Springer Berlin Heidelberg. : Navigli, R. 2009. "Word sense disambiguation: A survey", en ACM Computing Surveys 41 (2), pp. 1-69. : Palmer, M., Fellbaum, C., Cotton, S., Delfs, L. & Dang, H. T. (2001). English tasks: All-words and verb lexical sample. The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems (pp. 21-24). Association for Computational Linguistics. : Patwardhan, S., Banerjee, S. & Pedersen, T. (2003). Using measures of semantic relatedness for word sense disambiguation. International Conference on Intelligent Text Processing and Computational Linguistics (pp. 241-257). Springer Berlin Heidelberg. : Pedersen, T. 2006. Unsupervised Corpus-Based Methods for WSD. In P. E. Eneko Agirre (Ed.), Word Sense Disambiguation, Algorithms and Applications. Springer, pp. 133-166. : Pedersen, T., & Mihalcea, R. 2005. Advances in Word Sense Disambiguation. Paper presented at the Association for Computational Linguistics (ACL'05). : Pham, T. P., Ng, H. T. & Lee, W. S. (2005). Word sense disambiguation with semi-supervised learning. Proceedings of the National Conference on Artificial Intelligence, 20(3), 1093. : Rezapour, A. R., Fakhrahmad, S. M. & Sadreddini, M. H. (2011). Applying weighted KNN to word sense disambiguation. Proceedings of the World Congress on Engineering, 3, 6-8. : Sinha, R. & Mihalcea R. (2007). Unsupervised graph-basedword sense disambiguation using measures of word semantic similarity. Proceedings of the Semantic Computing (ICSC), 2007 IEEE International Conference (pp. 363-369). California: Irvine. : Stevenson, M. 2003. Word Sense Disambiguation: The case for combinations of Knowledge Sources. Standford: CSLI Publications. : Taghipour, K. & Ng, H. T. (2015). Semi-supervised word sense disambiguation using word embeddings in general and specific domains. Proceedings of NAACL HLT 2015, 314-323. : Wang, T. & Hirst, G. (2014). Applying a Naive Bayes Similarity Measure to Word Sense Disambiguation. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Short Papers) (pp. 531-537). Association for Computational Linguistics. : Wang, T., Rao, J. & Hu, Q. (2014). Supervised word sense disambiguation using semantic diffusion kernel. Engineering Applications of Artificial Intelligence, 27, 167-174. : Yuan, D., Doherty, R., Richardson, J., Evans, C. & Altendorf, E. (2016). Word sense disambiguation with neural language models. arXiv preprint arXiv:1603.07012. : Zhong, Z. & Ng, H. T. (2012). Word sense disambiguation improves information retrieval. Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers -Volume 1 (pp. 273-282). Association for Computational Linguistics. |