Improving the identification effect of technical trajectory by adding ghost edges in the patent citation network

Abstract

This paper proposes a method to improve the identification effect of technical Trajectory by adding ghost edges in the patent citation network, which includes calculating patent technology similarity, constructing ghost edge candidate set, adding the ghost edges by evaluating the utility measures, and using main path analysis to identify four technical trajectories. Taking US e-commerce data technology as an example, we find the following three points. (1) Adding a small amount of ghost edges in the patent citation network helps to increase the accuracy of technical trajectory identification, but adding a large number of ghost edges may cause destructive effects on the network structure and lead to identification bias. The experience value of this case is at most 10%. (2) Different construction methods of ghost edge candidate sets will have an important impact on the result of improving the trajectory recognition. No matter which candidate set is used, there is no deviation in the primary technical trajectory identification. However, there are differences in the subsequent technical trajectory identification. (3) The addition of the ghost edges further improves the network characteristics, especially the technical trajectory differences in subsequent locations which are identified.