Arabic question-answering via instance based learning from an FAQ corpus

In this paper, we describe a way to access Arabic information using chatbot, without the need for sophisticated natural language processing or logical inference. FAQs are Frequently-Asked Questions documents, designed to capture the logical ontology of a given domain. Any Natural Language interface to an FAQ is constrained to reply with the given Answers, so there is no need for NL generation to recreate well-formed answers, or for deep analysis or logical inference to map user input questions onto this logical ontology; simple (but large) set of pattern-template matching rules will suffice. In previous research, this works properly with English and other European languages. In this paper, we try to see how the same chatbot will react in terms of Arabic FAQs. Initial results shows that 93% of answers were correct, but because of a lot of characteristics related to Arabic language, changing Arabic questions into other forms may lead to no answers.