Question classification is one of the first tasks carried out in a Question Answering system. In this paper we present a multilingual question classification system based on machine learning techniques. We use Support Vector Machines to classify the questions. All the features needed to train and test this method are automatically extracted through statistical information in an unsupervised way, comparing Poisson distributions of single words in two plain corpora of questions and documents. Thus, we need nothing but plain text to train the system, obtaining a flexible approach easy to adapt to new languages and domains. We have tested it on a bilingual corpus of questions in English and Spanish. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Tomás, D., Vicedo, J. L., Bisbal, E., & Moreno, L. (2006). Automatic feature extraction for question classification based on dissimilarity of probability distributions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4139 LNAI, pp. 133–140). Springer Verlag. https://doi.org/10.1007/11816508_15
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