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- W2753240178 abstract "Online Question Answering Communities (Q& A C) provide a valuable amount of information in several topics. The major challenge with Q& A C is the detection of the authoritative users. When manipulating real world data, we have to deal with imperfections and uncertainty that can occur. In this paper, we propose a belief measure of expertise allowing us to detect users with the highest degree of expertise based on their attributes. Experiments on a dataset from a large online Q&A Community prove that the proposed model can be used to improve the identification of most expert users." @default.
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- W2753240178 date "2017-01-01" @default.
- W2753240178 modified "2023-09-23" @default.
- W2753240178 title "Belief Measure of Expertise for Experts Detection in Question Answering Communities: case study Stack Overflow" @default.
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- W2753240178 doi "https://doi.org/10.1016/j.procs.2017.08.099" @default.
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