This paper proposes a three-stage framework to automatically create expertise profiles for members of online communities, crucial for harnessing global knowledge. The framework estimates document-topic relevance and user-document association to calculate individual topic expertise levels, comparing two information retrieval techniques against an LDA-based model. It also examines the effectiveness of a filtering strategy in enhancing expert profiling. Experimental results from two real datasets offer insights into selecting optimal models for accurately profiling users' expertise in various global online communities.
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Liu, Xiaomo, et al. "Harnessing global expertise: A comparative study of expertise profiling methods for online communities." Information Systems Frontiers 16 (2014): 715-727.
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