We present CORDER (COmmunity Relation Discovery by named Entity Recognition) an un-supervised machine learning algorithm that exploits named entity recognition and co-occurrence data to associate individuals in an organization with their expertise and associates. We
discuss the problems associated with evaluating
unsupervised learners and report our initial evaluation
experiments
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