The nature of statistical learning theory
The nature of statistical learning theory
Foundations of statistical natural language processing
Foundations of statistical natural language processing
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Parsing and question classification for question answering
ODQA '01 Proceedings of the workshop on Open-domain question answering - Volume 12
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
A multilingual SVM-based question classification system
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
A semantic approach for question classification using WordNet and Wikipedia
Pattern Recognition Letters
Re-ranking passages with LSA in a question answering system
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
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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.