Turkish question answering application with course-grained semantic matrix representation of sentences

In this paper a novel powerful method for Information Retrieval based Factoid Question Answering system is proposed. A factoid question has exactly one correct answer, and the answer is mostly a named entity like person, date, location etc. A rule-based method for question classification, query formulation and answer processing methods are explored based on our coarse-grained semantic representation for Turkish sentences. “HazırCevap” Question Answering Application which is intended for high-school students to support their education is used to evaluate the proposed method. Testing with a set of questions of HazırCevap dataset, the proposed Question Answering system scored 7.6% for Top5 accuracy, 12.6% for Top10 accuracy and 7.4% for Top20 accuracy which is minimum 7% higher than previ2ous state of the art method.