面向观众群落个性化需求的文化演出服务建模与推荐
发布时间：2018-08-01 10:13
【摘要】：近些年，随着人们对精神文化的不断追求，，以及国家对文化产业的大力支持，文化演出服务行业随之繁荣。文化演出服务提供者提供的资源日益丰富，观众的需求偏好日益个性化，如何将丰富的文化演出服务资源进行选择与组合，使其满足观众的需求是亟待解决的问题。与此同时，社交网络逐渐成为热点，大量网民涌入社交网络，其中不乏文化演出的忠实观众。因此，如何从社交网络中挖掘出观众需求，为其推荐文化演出也具有重要意义。本文针对以上两点进行研究，提出了面向观众群落个性化需求的文化演出服务建模与推荐方法。 首先，为了支持后续的文化演出服务的定制与推荐，在建立可定制模型时识别服务的可配置点。这些可定制模型包括：价值网、BPMN模型、资源模型以及GRAI模型。在以上模型以及得到的可配置点的基础上，建立起观众特征、演出特征以及票务服务特征之间的关系，形成贝叶斯网络。 然后，为了帮助发现潜在的观众，以社交网络为工具，从中获取观众节点以及观众特征，并以社交网络为演出信息传输的平台，向观众推送演出。为了提高观众对演出的兴趣度，增强推送的效果，提出了附加演出特征的优化选择算法。该算法主要用于从文化演出的多个演出特征中选择出被推送的观众最可能感兴趣的演出特征，附加在演出信息中。 其次，为了发现不同群体的观众的个性化需求，将在社交网络中推送演出后得到的传播树划分为多个观众群落，以观众群落为一个整体，向其提供个性化的文化演出服务。由此，减轻文化演出服务提供者为成百上千的观众提供个性化服务的负担。 再则，为了提高观众对文化演出服务的满意度以及对服务企业的忠诚度，提出针对观众群落的个性化需求提供个性化的文化演出服务。将文化演出服务分为票务服务和演出服务，分别采用贝叶斯网络方法和层次分析法进行解决。 最后，为了验证以上理论的可行性，开发了文化演出服务推荐系统。该系统包含模块：模拟演出信息在社交网络中的自然传播、模拟演出信息在社交网络中的推送传播、观众群落及其需求的发现、个性化票务服务方案的生成。
[Abstract]:In recent years, with the constant pursuit of spiritual culture and the strong support of the country to the cultural industry, the cultural performance service industry has flourished. Cultural performance service providers provide more and more resources and audience's demand preferences become more and more individualized. How to select and combine the rich cultural performance service resources to meet the needs of the audience is an urgent problem to be solved. At the same time, social networks gradually become a hot spot, with a large number of Internet users, including loyal audience of cultural performances. Therefore, how to dig out audience needs from social networks and recommend cultural performances for them is also of great significance. Aiming at the above two points, this paper puts forward a method of modeling and recommending cultural performance service to meet the individual needs of audience community. Firstly, in order to support the customization and recommendation of the subsequent cultural performance service, the configurable points of the service are identified when the customizable model is established. These customizable models include: value net BPMN model, resource model and GRAI model. On the basis of the above model and the configurable points, the relationship among audience features, performance features and ticket service features is established to form a Bayesian network. Then, in order to help find potential audience, social network is used as a tool to obtain audience nodes and audience characteristics, and social network is used as the platform of performance information transmission to push the performance to the audience. In order to improve the audience's interest in the performance and enhance the effect of push, an optimal selection algorithm for additional performance features is proposed. The algorithm is mainly used to select the most interesting performance features of the pushed audience from the multiple performance features of the cultural performance and attach them to the performance information. Secondly, in order to find out the individual needs of different groups of audience, the communication tree obtained after pushing the performance in social network is divided into multiple audience groups, and the audience community is taken as a whole to provide individualized cultural performance services to them. This reduces the burden on cultural performance service providers to provide personalized services to hundreds of viewers. Furthermore, in order to improve the satisfaction of the audience to the cultural performance service and the loyalty to the service enterprises, it is proposed to provide individualized cultural performance service for the audience community. The cultural performance service is divided into ticketing service and performance service, which are solved by Bayesian network method and analytic hierarchy process. Finally, in order to verify the feasibility of the above theory, a cultural performance service recommendation system is developed. The system includes modules: simulating the natural transmission of performance information in the social network, simulating the push transmission of the performance information in the social network, discovering the audience community and its needs, and generating the individualized ticket service scheme.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.09
本文编号：2157242
[Abstract]:In recent years, with the constant pursuit of spiritual culture and the strong support of the country to the cultural industry, the cultural performance service industry has flourished. Cultural performance service providers provide more and more resources and audience's demand preferences become more and more individualized. How to select and combine the rich cultural performance service resources to meet the needs of the audience is an urgent problem to be solved. At the same time, social networks gradually become a hot spot, with a large number of Internet users, including loyal audience of cultural performances. Therefore, how to dig out audience needs from social networks and recommend cultural performances for them is also of great significance. Aiming at the above two points, this paper puts forward a method of modeling and recommending cultural performance service to meet the individual needs of audience community. Firstly, in order to support the customization and recommendation of the subsequent cultural performance service, the configurable points of the service are identified when the customizable model is established. These customizable models include: value net BPMN model, resource model and GRAI model. On the basis of the above model and the configurable points, the relationship among audience features, performance features and ticket service features is established to form a Bayesian network. Then, in order to help find potential audience, social network is used as a tool to obtain audience nodes and audience characteristics, and social network is used as the platform of performance information transmission to push the performance to the audience. In order to improve the audience's interest in the performance and enhance the effect of push, an optimal selection algorithm for additional performance features is proposed. The algorithm is mainly used to select the most interesting performance features of the pushed audience from the multiple performance features of the cultural performance and attach them to the performance information. Secondly, in order to find out the individual needs of different groups of audience, the communication tree obtained after pushing the performance in social network is divided into multiple audience groups, and the audience community is taken as a whole to provide individualized cultural performance services to them. This reduces the burden on cultural performance service providers to provide personalized services to hundreds of viewers. Furthermore, in order to improve the satisfaction of the audience to the cultural performance service and the loyalty to the service enterprises, it is proposed to provide individualized cultural performance service for the audience community. The cultural performance service is divided into ticketing service and performance service, which are solved by Bayesian network method and analytic hierarchy process. Finally, in order to verify the feasibility of the above theory, a cultural performance service recommendation system is developed. The system includes modules: simulating the natural transmission of performance information in the social network, simulating the push transmission of the performance information in the social network, discovering the audience community and its needs, and generating the individualized ticket service scheme.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.09
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