Finding Experts by Link Prediction in Co-authorship Networks

Speaker: Milen Pavlov

Research collaborations are always encouraged, as they often yield good results. However, researcher networks contain massive amounts of experts in various disciplines and it is difficult for the individual researcher to decide which experts will match his own expertise best. As a result, often collaboration outcomes are uncertain and research teams are poorly organized. We propose a method for building link predictors in social networks, where nodes can represent researchers and links - collaborations. In this case, predictors might offer good suggestions for future collaborations. We test our method on a researcher co-authorship network and obtain link predictors of encouraging accuracy. This leads us to believe our method could be useful in building and maintaining strong research teams. It could also help with choosing vocabulary for expert description, since link predictors contain implicit information about which structural attributes of the network are important with respect to the link prediction problem.

The full paper will appear in Proc. ISWC 2007 FEWS