With the continuous development of the industrial Internet, big data and artificial intelligence contribute to the comprehensive interconnection in human-cyber-physical system. The amount of task data generated by users using the service is growing exponentially. While recommending services for online users to meet personalized needs, and for services that need to be completed through human- cyber-physical interaction, it has become a challenging problem how to integrate the various offline and online resources to dispatch the right person to complete the task quickly and effectively. In order to ensure the accuracy of services dispatch, this study proposes a cross-domain collaborative service dispatch method that takes into account the data characteristics of all these factors in human-cyber-physical system. In order to get a more reasonable dispatch, the sentiment characteristics of user evaluation and the similarity of business data are analyzed respectively, and then the attributes inherent in the real world are added of which have an impact on business processes. Finally, taking the doctor-patient assignment of an online diagnosis and treatment platform on the Internet as an example, the results show that the method proposed in this study has high accuracy and can improve the efficiency of task execution.