基于社会网络的民航旅客价值发现方法研究
发布时间：2019-06-28 14:40
【摘要】：随着民航信息化的不断深入,系统积累了大量的旅客信息数据,如何有效地利用这些数据服务于民航业,是个迫切的任务.传统的民航旅客价值分析重点针对单个旅客,忽略了旅客间的关系,然而,现实生活中,旅客之间是存在相互影响的.社会网络研究在于考虑每个节点价值的同时也把节点间的联系进行量化.本文主要是利用社会网络的相关知识,分析旅客间内在关系,构建民航旅客社会网络并挖掘出有价值的旅客,为企业市场营销提供决策支持,有利于民航企业提高服务质量,同时旅客也因此获得更具针对性的优质的航空服务.首先本文提出了一种基于PNR数据间关系,构建民航旅客社会网络的方法,并且利用某航空公司多条航线上的旅客出行记录进行实验,提取出了网络中最大的连通子图,为进一步研究网络节点的价值(重要节点)提供有利的实验基础.其次为了更精确查找网络中有价值的节点(重要节点),在研究与比较了多种模型的基础上,本文提出了一种基于多层次灰色关联分析的民航旅客社会网络价值发现模型.考虑到普通聚类系数不能衡量聚类的规模,提出了修正的聚类系数;建立多层次-灰色关联分析模型,实现对网络节点的排序.把该模型应用在民航旅客社会网络中,得到了理想的结果,通过与实际情况对比,进一步验证了模型的可靠性.最后本文提出基于重要节点发现算法的民航旅客社会网络价值模型,主要是研究了系统科学,网络关系和互联网搜索这三个领域中的四种代表算法,并采用F-度量的方法对计算结果进行比较,筛选出重要的节点,通过度,二重度,点权,二重点权指标对节点的可靠性进行分析,找出了每个连通子图中的重要节点.综上所述,本文主要构建基于PNR数据的民航旅客社会网络,提出基于多层次灰色关联分析模型与基于重要节点发现算法的民航旅客社会网络价值模型,模型仿真的应用表明,可以发现有价值的旅客,为航空公司的决策提供帮助,通过对高价值旅客的专门营销,实现以最小代价达到最大利益,从而为航空公司节约成本.
[Abstract]:With the deepening of civil aviation informatization, the system has accumulated a large number of passenger information data, how to effectively use these data to serve the civil aviation industry, is an urgent task. The traditional civil aviation passenger value analysis focuses on a single passenger, neglecting the relationship between passengers. However, in real life, there is interaction between passengers. The research of social network is to consider the value of each node, but also to quantify the relationship between nodes. This paper mainly uses the relevant knowledge of social network to analyze the relationship between passengers, construct the social network of civil aviation passengers and excavate valuable passengers, and provide decision support for enterprise marketing, which is helpful for civil aviation enterprises to improve the service quality, and at the same time, passengers also obtain more targeted and high quality aviation services. Firstly, this paper proposes a method to construct civil aviation passenger social network based on the relationship between PNR data, and uses the passenger travel records of multiple routes of an airline to extract the largest connected subgraph in the network, which provides a favorable experimental basis for further study of the value of network nodes (important nodes). Secondly, in order to find valuable nodes (important nodes) more accurately, based on the research and comparison of various models, this paper proposes a value discovery model of civil aviation passenger social network based on multi-level grey relational analysis. Considering that the ordinary clustering coefficient can not measure the scale of clustering, a modified clustering coefficient is proposed, and a multi-level grey relational analysis model is established to sort the network nodes. The model is applied to the social network of civil aviation passengers, and the ideal results are obtained. by comparing with the actual situation, the reliability of the model is further verified. Finally, this paper proposes a social network value model of civil aviation passengers based on important node discovery algorithm, which mainly studies four representative algorithms in three fields: system science, network relationship and Internet search, and compares the calculation results with the method of F-metric, and selects out the important nodes, and analyzes the reliability of the nodes through the degree of passing, the second degree, the point weight and the double point weight index. The important nodes in each connected subgraph are found out. To sum up, this paper mainly constructs the civil aviation passenger social network based on PNR data, and puts forward the civil aviation passenger social network value model based on the multi-level grey relational analysis model and the important node discovery algorithm. The application of the model simulation shows that valuable passengers can be found, which can provide help for airlines to make decisions. Through the special marketing of high-value passengers, the maximum interests can be achieved at the minimum cost. In order to save costs for airlines.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：V354;TP393.09
[Abstract]:With the deepening of civil aviation informatization, the system has accumulated a large number of passenger information data, how to effectively use these data to serve the civil aviation industry, is an urgent task. The traditional civil aviation passenger value analysis focuses on a single passenger, neglecting the relationship between passengers. However, in real life, there is interaction between passengers. The research of social network is to consider the value of each node, but also to quantify the relationship between nodes. This paper mainly uses the relevant knowledge of social network to analyze the relationship between passengers, construct the social network of civil aviation passengers and excavate valuable passengers, and provide decision support for enterprise marketing, which is helpful for civil aviation enterprises to improve the service quality, and at the same time, passengers also obtain more targeted and high quality aviation services. Firstly, this paper proposes a method to construct civil aviation passenger social network based on the relationship between PNR data, and uses the passenger travel records of multiple routes of an airline to extract the largest connected subgraph in the network, which provides a favorable experimental basis for further study of the value of network nodes (important nodes). Secondly, in order to find valuable nodes (important nodes) more accurately, based on the research and comparison of various models, this paper proposes a value discovery model of civil aviation passenger social network based on multi-level grey relational analysis. Considering that the ordinary clustering coefficient can not measure the scale of clustering, a modified clustering coefficient is proposed, and a multi-level grey relational analysis model is established to sort the network nodes. The model is applied to the social network of civil aviation passengers, and the ideal results are obtained. by comparing with the actual situation, the reliability of the model is further verified. Finally, this paper proposes a social network value model of civil aviation passengers based on important node discovery algorithm, which mainly studies four representative algorithms in three fields: system science, network relationship and Internet search, and compares the calculation results with the method of F-metric, and selects out the important nodes, and analyzes the reliability of the nodes through the degree of passing, the second degree, the point weight and the double point weight index. The important nodes in each connected subgraph are found out. To sum up, this paper mainly constructs the civil aviation passenger social network based on PNR data, and puts forward the civil aviation passenger social network value model based on the multi-level grey relational analysis model and the important node discovery algorithm. The application of the model simulation shows that valuable passengers can be found, which can provide help for airlines to make decisions. Through the special marketing of high-value passengers, the maximum interests can be achieved at the minimum cost. In order to save costs for airlines.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：V354;TP393.09
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