Early Detection Of Topical Expertise In Community Question Answering
SIGIR '15: The 38th International ACM SIGIR conference on research and development in Information Retrieval Santiago Chile August, 2015(2015)
摘要
We focus on detecting potential topical experts in community question answering platforms early on in their lifecycle. We use a semi supervised machine learning approach. We extract three types of feature: (i) textual, (ii) behavioral, and (iii) time-aware, which we use to predict whether a user will become an expert in the longterm. We compare our method to a machine learning method based on a state-of-the-art method in expertise retrieval. Results on data from Stack Overflow demonstrate the utility of adding behavioral and time-aware features to the baseline method with a net improvement in accuracy of 26% for very early detection of expertise.
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关键词
Community question answering,User profiling,Expertise finding
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