Answer Extraction for how and why Questions in Question Answering Systems

With the increasing amount of Arabic text on the web and in the information repositories and the demand of users to have specific answers to their questions, the need for Question Answering (QA) Systems became a necessity. Our Question Answering System answers two types of Questions: How and Why Questions. The system takes a question given in natural language expressed in the Arabic language and attempts to produce concise answers. The system's main source of knowledge is a collection of Arabic text documents extracted from the Arabic Wikipedia. The reasons behind developing this system is due to the absence of Arabic Questions Answering Systems(QASs) which deals with How and Why questions and this is because of the complexity of extracting the answers that satisfy this type of questions. Information Retrieval (IR) module is used to retrieve the target document from the corpus. The IR is coupled with Natural Language (NLP) Tools to process the given question and to extract the answer. The major goal of the proposed system is to extract the passage which is likely to contain the answer based on the semantic similarity between question keywords and the sentences of the passage. We used Precision, Recall and F1 Measure to calculate the accuracy of the system.