Predicting Best Answer in Community Question Answering System Using Naive Bayes Algorithm

Abstract

Community question answering sites are eminent online community that has bring along users to another milestone of knowledge provision to let the users ask queries. There are number of increasing questions that get posted but may not get fixed in short amount of time as domain expert may not find questions that he/she is capable of answering and also finding the best answer among multiple answers is another challenge. Hence, we propose a new technique to question routing system using text classification Naive Bayes algorithm and Natural Language Processing technique. This system provides technical and non-technical communities both. Every community have experts provided, which will answer the questions routed to them. Propose system mainly works on ranking of answers and ratings given by user to find the best answer. Ranking is achieved through ratings given by the users. In some of conditions unsatisfied answers on system get resolve by online forum with direct communication between the expert and user.