QA system to guide citizens to reliable health information Sarah CRUCHET, Health On the Net foundation 24 rue Micheli du Crest

Many attempts have been made in the QA domain but no system applicable to the field of health is currently available on the Internet. This paper describes a multilingual QA system adapted to the health domain and more particularly to the detection of the question’s model which has a greater effect on the rest of the QA system. Our original hypothesis is that a question can be defined by two criteria: type of expected answer and medical type. These two must appear in the step of detection of the model question and thus, the corresponding answer. For this, questions were searched on the Internet and then given to experts in order to obtain classifications according to criteria mentioned above. In addition, tests of supervised and non-supervised classification were made to determine features of questions. Results of this first step were that algorithms of classification were chosen. They showed that categorizers giving the best results were the SVM. Currently, for a set of 100 questions, 84 are well categorized in English and 68 in French according to the type of expected answer. These figures fall to less than 50 % for the medical type. Evaluations have showed that the system was good to identify the type of expected answer and could be enhanced for the medical type. It leads us to use an external source of knowledge: UMLS. A future improvement will be the usage of UMLS semantic network to better categorize a query according to the medical domain