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Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets.
Presented at CSTA workshop, CIKM 2013,
October 28, 2013