Kweri ME: A Q&A based model which predicts the accepted answers of questions in CQA sites

Abstract

An approach to find the best answers from the multiple answer posted for given question in Community Question Answering(CQA) sites is tedious and most time consuming if manual process used. And also the experts are required to do this by analysis all given answers. So we presented an new approach based on topic modeling and classifier. To evaluate correctness of the proposed model, a set of parameters are used, such as Receiver Operating Characteristics Area Under Curve, Precision Recall Area Under Curve, Confussion matrix, F1 score and Accuracy. Results show that the proposed model is effective in predicting the best answer.