面向觀眾群落個性化需求的文化演出服務建模與推薦
發(fā)布時間：2018-08-01 10:13
【摘要】：近些年，隨著人們對精神文化的不斷追求，，以及國家對文化產(chǎn)業(yè)的大力支持，文化演出服務行業(yè)隨之繁榮。文化演出服務提供者提供的資源日益豐富，觀眾的需求偏好日益?zhèn)�性化，如何將豐富的文化演出服務資源進行選擇與組合，使其滿足觀眾的需求是亟待解決的問題。與此同時，社交網(wǎng)絡逐漸成為熱點，大量網(wǎng)民涌入社交網(wǎng)絡，其中不乏文化演出的忠實觀眾。因此，如何從社交網(wǎng)絡中挖掘出觀眾需求，為其推薦文化演出也具有重要意義。本文針對以上兩點進行研究，提出了面向觀眾群落個性化需求的文化演出服務建模與推薦方法。 首先，為了支持后續(xù)的文化演出服務的定制與推薦，在建立可定制模型時識別服務的可配置點。這些可定制模型包括：價值網(wǎng)、BPMN模型、資源模型以及GRAI模型。在以上模型以及得到的可配置點的基礎上，建立起觀眾特征、演出特征以及票務服務特征之間的關系，形成貝葉斯網(wǎng)絡。 然后，為了幫助發(fā)現(xiàn)潛在的觀眾，以社交網(wǎng)絡為工具，從中獲取觀眾節(jié)點以及觀眾特征，并以社交網(wǎng)絡為演出信息傳輸?shù)钠脚_，向觀眾推送演出。為了提高觀眾對演出的興趣度，增強推送的效果，提出了附加演出特征的優(yōu)化選擇算法。該算法主要用于從文化演出的多個演出特征中選擇出被推送的觀眾最可能感興趣的演出特征，附加在演出信息中。 其次，為了發(fā)現(xiàn)不同群體的觀眾的個性化需求，將在社交網(wǎng)絡中推送演出后得到的傳播樹劃分為多個觀眾群落，以觀眾群落為一個整體，向其提供個性化的文化演出服務。由此，減輕文化演出服務提供者為成百上千的觀眾提供個性化服務的負擔。 再則，為了提高觀眾對文化演出服務的滿意度以及對服務企業(yè)的忠誠度，提出針對觀眾群落的個性化需求提供個性化的文化演出服務。將文化演出服務分為票務服務和演出服務，分別采用貝葉斯網(wǎng)絡方法和層次分析法進行解決。 最后，為了驗證以上理論的可行性，開發(fā)了文化演出服務推薦系統(tǒng)。該系統(tǒng)包含模塊：模擬演出信息在社交網(wǎng)絡中的自然傳播、模擬演出信息在社交網(wǎng)絡中的推送傳播、觀眾群落及其需求的發(fā)現(xiàn)、個性化票務服務方案的生成。
[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.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.09
本文編號：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.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.09
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