The rapid development of Community Question Answering (CQA) satisfies users' quest for
professional and personal knowledge about anything. In CQA, one central issue is to find …

Understanding people's expertise is not a trivial task since it is time-consuming when
manually executed. Automated approaches have become a topic of research in recent years …

Expert finding for question answering is a challenging problem in community-based
question answering (CQA) systems, arising in many real applications such as question …

Hidden Markov modeling is a probabilistic technique for the study of time series. Hidden
Markov theory permits modeling with many of the classical probability distributions. The …

Community question answering (CQA) represents the type of Web applications where
people can exchange knowledge via asking and answering questions. One significant …

Expert finding for question answering is a challenging problem in Community-based
Question Answering (CQA) site, arising in many applications such as question routing and …

Directed graphs have been widely used in Community Question Answering services (CQAs)
to model asymmetric relationships among different types of nodes in CQA graphs, eg …

With the high mobility of talent, it becomes critical for the recruitment team to find the right
talent from the right source in an efficient manner. The prevalence of Online Professional …

Expert finding is an important research field in community question answering (CQA).
Traditional expert finding methods mainly exploit topic analysis and authority calculation …

Abstract In Community Question Answering (CQA) websites, expert finding aims to seek
relevant experts for answering questions. The core of expert finding is to match candidate …