  The purpose of this study is to investigate the structure and evolution of
knowledge spillovers across technological domains. Specifically, dynamic
patterns of knowledge flow among 29 technological domains, measured by patent
citations for eight distinct periods, are identified and link prediction is
tested for capability for forecasting the evolution in these cross-domain
patent networks. The overall success of the predictions using the Katz metric
implies that there is a tendency to generate increased knowledge flows mostly
within the set of previously linked technological domains. This study
contributes to innovation studies by characterizing the structural change and
evolutionary behaviors in dynamic technology networks and by offering the basis
for predicting the emergence of future technological knowledge flows.
