Processing Medical Binary Questions in Standard Arabic Using NooJ

Nowadays, the medical domain has a high volume of electronic documents. The exploitation of this large quantity of data makes the search of specific information complex and time consuming. This difficulty has prompted the development of new adapted research tools, as question-answering systems. Indeed, this type of system allows a user to ask a question in natural language and automatically identify a specific answer instead of a set of documents deemed pertinent, as is the case with search engines. For this purpose, we are developing a question answering system which is based on a linguistic approach. The use of the linguistic engine of NooJ in order to formalize the automatic recognition rules and then applying them to a dynamic corpus composed of arabic medical journalistic articles. In this paper, we present a method for analyzing medical Binary questions. The analysis of the question asked by the user by means the application of cascade of morpho-syntactic resources. The linguistic patterns (grammars) which allow us to annotate the question and the semantic features of the question of extracting the focus and topic of the question. We start with the implementation of the rules which identify and to annotate the various medical entities. The named entity recognizer (NER) is able to find references to people, places and organizations, diseases, viruses, as targets to extract the correct answer from the user. The NER is embedded in our question answering system in order to identify the answer and delimit the potential justification sequence the precision and recall show that the actual results are encouraging and could be integrated for more types of questions other than binary questions.