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The purpose of this study is to investigate the structure and evolution ofknowledge spillovers across technological domains. Specifically, dynamicpatterns of knowledge flow among 29 technological domains, measured by patentcitations for eight distinct periods, are identified and link prediction istested for capability for forecasting the evolution in these cross-domainpatent networks. The overall success of the predictions using the Katz metricimplies that there is a tendency to generate increased knowledge flows mostlywithin the set of previously linked technological domains. This studycontributes to innovation studies by characterizing the structural change andevolutionary behaviors in dynamic technology networks and by offering the basisfor predicting the emergence of future technological knowledge flows.

Dynamic patterns of knowledge flows across technological domains: empirical results and link prediction