SEMEF: A Taxonomy-Based Discovery of Experts, Expertise and Collaboration Networks

Finding relevant experts in research is often critical and essential for collaboration. Semantics can be useful in this process. In particular, a taxonomy of Computer Science topics, together with an ontology of publications can be glued through explicit relationships from papers to one or more topics. These paper-totopics relationships, extracted from paper abstracts and keywords are valuable for building an Expertise Profile for a researcher based on the aggregation of the topics of his/her publications. We describe an approach that finds experts, expertise and collaboration networks in the context of the peer-review process. We use DBLP bibliography data to determine different levels of collaboration based on degrees of separation. This helps in suggesting experts for PC membership and has the benefit of presenting potentially unknown experts to the PC Chair(s). We present our findings and evaluations in the context of expanding collaboration networks in a peerreview setting.