Research on the Prediction Method of Inter-Firm Technological Innovation Cooperation Based on Multiple Integration
The method of predicting reasonable technology innovation cooperation is an effective approach for enterprises to identify suit-able partners in technology innovation,thereby enhancing their performance in this area.The present study utilizes enterprise patent data to construct a co-occurrence network of patent owners.It applies the Katz index to calculate the path similarity between enterprises,employs the TF-IDF algorithm to construct an enterprise keyword vector,calculates content similarity between enterprises using cosine similarity,and utilizes centrality indices from social network analysis methods to determine location similarity among enterprises.The enhanced integration of the three entities will unlock the collaborative potential among enterprises.Through the analysis of enterprise pa-tent data in the Graphene field,we predict potential collaborations between enterprises and demonstrate the effectiveness of this meth-od.The AUC index value is 0.7242,surpassing that of a single-index similarity recommendation method,thereby enhancing the accu-racy of suitable matches in collaboration recommendations.
万方数据
维普
