Detecting high-quality posts in community question answering sites

摘要: Community question answering (CQA) has become a new paradigm for seeking and sharing information. In CQA sites, users can ask answer questions, provide feedback (e.g., by voting or commenting) to these questions/answers. this article, we propose the early detection of high-quality Such help discover high-impact that would be widely recognized in as well identify useful gain much positive from site users. particular, view post quality perspective outcome. First, our key intuition is score an strongly positively correlated with its question, verify such correlation two real data sets. Second, armed verified correlation, family algorithms jointly detecting questions answers soon after they are posted sites. We conduct extensive experimental evaluations demonstrate effectiveness efficiency approaches. Overall, outperform best competitor prediction performance, while enjoying linear scalability respect total number posts.