关键词: 社团发现, 复杂网络, 专利网络, 创新态势, 启发式算法

Abstract:

The patent network, an important branch of the complex network, plays a significant guiding role in understanding and grasping the way of technological innovation. Patent text data is used to construct an undirected weighted patent network graph, an innovative situation analysis algorithm based on heuristic model of community detection is proposed. In order to alleviate the text vector sparse problem caused by patent title and abstract, an unsupervised sparse vector densification method is adopted. For automatic selection of similarity threshold in the process of patent network construction, an experimental driven method is used to compare the changing relationship between similarity threshold and common statistical indexes of patent network. The index of average clustering coefficient is selected to realize the automatic determination of the optimal similarity threshold. By using patent data in the field of digital China and big data, the validity of the method is verified and the innovation trends in the above field are analyzed.

Key words: community detection, complex network, patent network, innovation situation, heuristic algorithm