“EXPERTIFY” Finding Experts in Question and Answer Platforms

Abstract

Question and Answer (Q&A) platform are a growing mode of sharing knowledge. In a Q&A platform, a person can ask questions and one or many experts can provide answers. However, with the growth of user engagement in such platforms the experts who provide answers to questions have reduced. The quality of an answer is completely based on the expert, thus finding experts based on their interest and willingness to answer questions have become a commonly discussed topic. In this project, a developed system is introduced where it finds the most appropriate experts; who are not only in the domain of the question, but also express a likeness towards answering the giving question. The expert finding process involves few factors like tag-based interest, domain expertise, selection bias status and the ranking algorithm implemented by the solution to rank experts in order. Each of these processes are incorporated in developing this project to reach the final outcome of finding more reliable experts for users. Once a question is submitted to the Q&A platform, it searches for similar or tag-based questions, and then look for relevant experts. The program further classifies experts in a ranking order based on their previous answers and tendency of answering to similar questions. Then the user questions are directly targeted towards the selected experts, which results in obtaining quality answers within a lesser time.