Predicting Semantic Textual Similarity of Arabic Question Pairs using Deep Learning
Omar Einea, Ashraf Elnagar · 2019
Question pairing is the task of listing similar question-answer pairs to a query question automatically. This technique is used by famous online question-answering forums like Quora and Stack exchange, and has gotten a lot of attention lately as it reduces the amount of duplicate questions on such topics. That is why there are many researchers working on this task on the English language, but there is not much focus on other languages like the Arabic language. This paper introduces a deep neural networks based solution to the question pairing task on Arabic questions using minimal pre-processing. We investigate the best settings for the proposed DNN model. We show a thorough set of experiments and demonstrate that our proposed model outperforms the few existing implementations reported in literature on benchmark datasets by no less than 10% in prediction accuracy measure. Namely, the NSURL 2019 question-question dataset and the SemEval 2017 question-answer dataset. Our proposed model achieved 77% and 58% prediction accuracy on both datasets, respectively.