2009 · 11 citations · 18 references
ComputingComputer ScienceHuman-computer InteractionKnowledge RepresentationNatural Language ProcessingExpertise AnalyticsExpertise AssessmentExpertise DiscoveryExpertise RepresentationQuestion AnsweringDomain Expert FindingExpert RetrievalLink AnalysisQuestion Answering Systems
In this paper, we propose a latent link analysis approach for improving the accuracy of expert finding in user-interactive question answering (UIQA) services. Both direct and latent relationship links are considered in the link analysis of the user relation graph model. In the graph model, the direct links can be acquired directly from question-answer relationship between users. While the latent links, which reveal the latent question-answer relation between users, can be obtained indirectly by measuring the similarity between users' asked and answered question profiles. Finally, a propagation-based approach is employed to calculate the expert score for evaluating users' expertise levels. Experimental results show that our approach can perform better than the method without considering latent relationship links in terms of expert finding and ranking.
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