Constraint Inversion Model of Core Science Complex Network

Abstract

In order to reduce the research costs, increase the efficiency of scientific researches, and improve the inversion abilities of core technologies, in the paper, a constrained inversion model aiming at tracking the source of core technology was proposed. Firstly, a complex network was built and it treated the most important product or technology as the core node vector. In the network, the social and technical attributes of the product were assigned as the elements of the core node vector. Therefore, the relationships among the core node and other nodes represented connective strength which were fairly important for calculating the path weights. Essentially, the weights were integrated attributes derive from a called score matrix. Then a constrained optimization criterion was employed to evaluate the scores of paths so that the best optimal path was determined. For reducing the number of searching and the times of calculating, all the constraints relationships of node vectors were classified into several types. The experimental results demonstrate that the proposed approach has a superior performance against the current state-of-the art methods over a real case.