Title: A weighted knowledge super network model for collaborative product innovation based on adjacency matrix

Authors: Yanhua Wang; Fang Zhang

Addresses: Zhengzhou Shengda University of Economics, Business & Management, Zhengzhou 450000, China ' Zhengzhou Shengda University of Economics, Business & Management, Zhengzhou 450000, China

Abstract: Aiming at the problems existing in traditional methods such as poor destructibility, low knowledge processing capacity and easy loss of product innovation weighted knowledge, a collaborative product innovation weighted knowledge hypernetwork model based on adjacency matrix was designed. A knowledge sharing network model is established, which is used to transform product design tasks and form multiple sub-tasks. Acquire knowledge points and carry out network modelling, acquire the membership relationship between knowledge points, design individual knowledge subgraphs, and represent different knowledge subgraphs through adjacency matrix. The hypernetwork model is constructed, and the model is used to calculate knowledge points and relevant weights of knowledge, and the knowledge fusion is realised based on the calculation results, so as to realise the construction of knowledge hypernetwork model. The results show the maximum destruction resistance coefficient of the model is about 0.8, and the maximum product innovation weighted knowledge loss rate is only 15.2%.

Keywords: adjacency matrix; product innovation; hyper-network model; knowledge collaboration sharing; membership relationship; correlation weight.

DOI: 10.1504/IJPD.2021.116155

International Journal of Product Development, 2021 Vol.25 No.2, pp.200 - 212

Received: 27 Nov 2020
Accepted: 14 Mar 2021
Published online: 12 Jul 2021 *

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