Smart city next-gen social networks system based on software reconstruction model and cognitive computing

Social network structure modeling is the basis of other fields of social network research, aiming to build a reasonable social network structure model. However, due to privacy protection and many other reasons, it is almost impossible to obtain all the data needed to construct the social network structure model, so it is necessary to study the use of incomplete data to construct the social network structure model. Although there are many methods to construct social network structure model, there are some problems. The research shows that human social group behavior shows some specific behavior patterns, and there are many corresponding structures and changes within the group. The main means adopted by smart city is information and communication technology to study, plan and sense multiple key information of urban internal operation system, that is, it can intelligently interact with different needs of public security, urban services, people's livelihood, environmental protection, industrial and commercial projects. The key lies in the adoption of high-end information sensing means, so that the city can operate and manage intelligently, improve the quality of life of urban people, and promote social harmony and long-term development. Therefore, this paper studies the next generation social network system of smart city based on software reconfiguration model and cognitive computing. We design the model based on the improvement of the traditional social networks to obtain the efficient representation and combine the software reconstruction model to improve the robustness. Through comparing the model with the state-of-the-art methods, the performance of the model is validated.