[KDD 2020] Enterprise Cooperation and Competition Analysis with Sign-Oriented Preference Network
Aug 13, 2020
The development of effective cooperative and competitive strategies,has been recognized as the key to the success of many companies,in a globalized world. Therefore, many efforts have been made,on the analysis of cooperation and competition among companies.,However, existing studies either rely on labor intensive empirical,analysis with specific cases or do not consider the heterogeneous,company information when quantitatively measuring company relationships in a company network. More importantly, it is not clear,how to generate a unified representation for cooperative and competitive strategies in a data driven way. To this end, in this paper,,we provide a large-scale data driven analysis on the cooperative and,competitive relationships among companies in a Sign-oriented Preference Network (SOPN). Specifically, we first exploit a Relational,Graph Convolutional Network (RGCN) for generating a deep representation of the heterogeneous company features and a company,relation network. Then, based on the representation, we generate,two sets of preference vectors for each company by utilizing the,attention mechanism to model the importance of different relations,,representing their cooperative and competitive strategies respectively. Also, we design a sign constraint to model the dependency,between cooperation and competition relations. Finally, we conduct extensive experiments on a real-world dataset, and verify the,effectiveness of our approach. Moreover, we provide a case study to,show some interesting patterns and their potential business value.
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