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.
