Developer Recommendation for Stack Exchange Software Engineering Q&A Website based on K-Means clustering and Developer Social Network Metric

Abstract Nowadays Online question answering website platforms are getting popular as it allows the users to get responses from varied experts beyond their reach. Businesses use these sites for their growth and exposure. Enormous volumes of question are posted on these sites. Finding an expert for answering large voluminous questions requires specialized techniques. This paper proposes hybrid approach for finding prominent expert for the posted questions. The proposed approach uses clustering and social network metrics. The approach clusters the database questions based on tag similarity using K Means. The new posted question is matched with the clusters and best suitable cluster is extracted. Developer Social Network is constructed for chosen cluster and Page Rank with time decay has been applied to find the prominent developer. The proposed approach attains 60% accuracy.