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In this paper, we evaluate a number of machine learning techniques for the task of ranking answers to why-questions. We use TF-IDF together with a set of 36 linguistically motivated features that characterize questions and answers. We experiment with a number of machine learning techniques (among which several classifiers and regression techniques, Ranking SVM and SVM map ) in various settings. The purpose of the experiments is to assess how the different machine learning approaches can copedoi:10.1007/s10791-010-9136-6 fatcat:pzoi5ntpqbd7hfjnnqfzh5gdve