
handle: 10045/1339
Este artículo presenta una aproximación multilingüe a la clasificación de preguntas basada en aprendizaje automático, empleando características de aprendizaje independientes del idioma. Esto va a permitir que el sistema sea flexible y fácilmente adaptable a nuevos idiomas. Sobre un corpus paralelo de preguntas en inglés y castellano, contrastaremos el rendimiento del sistema con tres métodos distintos de aprendizaje: Máquinas de Vectores Soporte, Máxima Entropía y aprendizaje basado en ejemplos.
This paper presents a multilingual approach to question classification based on machine learning. This approach is flexible and easy to adapt to new languages using language independent learning features. The system’s performance has been compared in a parallel English-Spanish corpus of questions using three different learning methods: Support Vector Machines, Maximum Entropy and Memory-based Learning.
Este trabajo ha sido subvencionado por el proyecto CICYT R2D2 (TIC2003-07158-C04) y por el Ministerio de Educación y Ciencia y el Fondo Social Europeo a través de la beca BES-2004-3935.
Question classification, Máxima entropía, Support vector machines, Multilingüe, Máquinas de vectores soporte, Aprendizaje automático, Clasificación de preguntas, Aprendizaje basado en ejemplos, Memory-based learning, Maximum entropy, Multilingual, Machine learning
Question classification, Máxima entropía, Support vector machines, Multilingüe, Máquinas de vectores soporte, Aprendizaje automático, Clasificación de preguntas, Aprendizaje basado en ejemplos, Memory-based learning, Maximum entropy, Multilingual, Machine learning
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