Update: February 24, 2023 The new version of Termout.org is now online, so this web site is now obsolete and will soon be dismantled. |
algorithm |
: Alfonseca, E. & Pérez, D. (2004). Automatic assessment of short questions with a Bleu-inspired algorithm and shallow NLP. Ponencia presentada en the 4th International Conference, EsTAL 2004, Alicante, España. : 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). : 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. : Keerthi, S., Shevade, S., Bhattacharyya, C. & Murthy, K. (2001). Improvements to Platt’s SMO Algorithm for SVM Classifier Design. Neural Computation, 13(3), 637-649. : Nazar, R. & Renau, I. (2016). A taxonomy of Spanish nouns, a statistical algorithm to generate it and its implementation in open source code. Ponencia presentada en el 10 th International Conference on Language Resources and Evaluation (LREC'16). European Language : Porter, M. F. (1980). An algorithm for suffix stripping. Program, 14, 130-137. : Qiang, G. (2010). An effective algorithm for improving the performance on naive Bayes for text classification. En International conference on computer research and development. Kuala Lumpur, Malasia. : Ramakrishnan, G., Prithviraj, B. & Bhattacharyya, P. (2004). A gloss-centered algorithm for disambiguation. Proceedings of SENSEVAL-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text. : Ramasubramanian, C. & Ramya, R. (2013). Effective pre-processing activities in text mining using improved porter’s stemming algorithm. International Journal of Advanced Research in Computer and Communication Engineering, 2(12), 2278-1021. : The statistical module of Atenea relies on the BiLingual Evaluation Understudy (BLEU) algorithm (Papineni, Roukos, Ward & Zhu, 2001). Basically, it looks for n-gram coincidences between the student's answer and the references. Its pseudocode is as follows: : Van Valin, R. D. Jr & Mairal, R. (2014). Interfacing the Lexicon and an Ontology in a Linking Algorithm. In M. A. Gómez, F. Ruiz de Mendoza-Ibáñez & F. Gonzálvez-García (Eds.), Theory and Practice in Functional-Cognitive Space (pp. 205-228). Amsterdam: John Benjamins . : Zhi-Hong, D., Tang, S.-W., Yang, D.-Q., Zhang, M., Wu, X. B. & Yang, M. (2002). Linear text classification algorithm based on category relevance factors. Ponencia presentada en el 5^th International Conference on Asian Digital Libra, Singapur. |