The invention discloses a fine-grained radio station audio content personalized organization recommendation method, which includes the steps of automatically segmenting and marking audio programs of a radio station according to semantics, mining user preferences based on the Internet big data, automatically arranging a personalized program list and real-timely pushing programs, and relates to the fields of audio processing, machine learning, big data analysis, recommendation systems, data mining and the like. According to the method, an algorithm process of automatically segmenting and marking traditional broadcast audio programs based on the semantics is provided, a technical scheme for personalized content recommendation based on the Internet big data is also provided, and a fine-grained audio content personalized organization recommendation method is achieved. According to the method disclosed by the invention, the cold start problem is integrated into account, the program list organization and generation, real-time program switching, real-time program push and other factors during the listening time of the user are combined, a simple mode that the current radio station transplants the FM live broadcast to the Internet streaming media for playback is changed, and from the view point of audience users, the needs that the users listen to the contents of interested programs at right time can be met.