Abstract
Transformation Based Learning (TBL) is an intensively Machine Learning algorithm frequently used in Natural Language Processing. TBL uses rule templates to identify error-correcting patterns. A critical requirement in TBL is the availability of a problem domain expert to build these rule templates. In this work, we propose an evolutionary approach based on Genetic Algorithms to automatically implement the template selection process. We show some empirical evidence that our approach provides template sets with almost the same quality as human built templates.
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Milidiú, R.L., Duarte, J.C., Nogueira dos Santos, C. (2007). TBL Template Selection: An Evolutionary Approach. In: Borrajo, D., Castillo, L., Corchado, J.M. (eds) Current Topics in Artificial Intelligence. CAEPIA 2007. Lecture Notes in Computer Science(), vol 4788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75271-4_19
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DOI: https://doi.org/10.1007/978-3-540-75271-4_19
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