Modeling And Combinatorial Optimization Of The Modern Cultural Performance Services Based On The Fourth Party Platform

Recent years, with the growth of people’s life level, people’s spiritual and cultural needs are growing.So cultural performances in our daily lives are becoming more and more popular.The number of cultural performances gradually increased, so decision-makings about the cultural performance are more difficult for cultural performances organizers.At the same time, the existing service platform pattern about the cultural performances are still the traditional tripartite pattern, such as damai, yipiaotong, etc. The traditional tripartite platform lack of effective integration of performance resources, ticketing resources and audience resources; Currently,cultural performance services still lack of the portrayal of business processes, value and the relationship between business processes and value; In addition, the existing PCN analysis combine the service’s model and value analysis, but merely gives a qualitative description of the value. In this paper, researches are focus on three points mentioned above: A quantitiative measure about the value of PCN analysis is given;Based on the users’ historical bahavior on cultural performances,the methods of predicting the screenings and the price of the single cultural performance and combining serval performances are putting forward;And we came up with the concept of the fourth-party platform ecosystem based on the cultural performances service.First of all, for the extension of PCN analysis method and the subsequent research,we established the PCN model of the whole life cycle of the single cultural performance.Based on the PCN model graph,the value model of the s ingle cultural performance is established. The value model includes: the activities mark model,the value statement model, the value mark model, the value dependency model and finally the method of measuring value. Thus, by combining the cultural performances service with the PCN analysis method, this paper gives a quantitative measure of the value of PCN analysis method.Secondly, extended research from a single cultural performance to cultural performance set.we gived the concept of fourth-party platform ecosystem.The fourth party platform ecosystem improves the existing tripartite pattern of the cultural performances. Then we gived the value network oriented participants and the value anlysis method of the fourth-party platform ecosystem.Then, by digging the user’s historical behavior on cultural performance service, we established the users’ behavior model and interest model. Combining clustering algorithm with the user’s interest model to cluster whole users.we analyzed the behavior of each cluster and extracted the interest features of each cluster. Based on the modeling and the value analysis about the single cultural performance and the cultural performances set on fourth-party platform ecosystem,we given the prediction methods for the price and the screening of the single performance and the combinatorial method of serval performances.Last but not least, we given the design and implementation of the system.The system includes the following three parts: We visualised the research we mentioned above using the webpage,including the performance classification tree,the users bahavior distribution diagram,the performance resources table, the value analysis area and the performance solutions area.Then we developed a PCN modeling tool using the GMF framework.Finally we developed a tail tickets management system based on the fourth-party platform.