基于社會網(wǎng)絡的民航旅客價值發(fā)現(xiàn)方法研究
發(fā)布時間：2019-06-28 14:40
【摘要】：隨著民航信息化的不斷深入,系統(tǒng)積累了大量的旅客信息數(shù)據(jù),如何有效地利用這些數(shù)據(jù)服務于民航業(yè),是個迫切的任務.傳統(tǒng)的民航旅客價值分析重點針對單個旅客,忽略了旅客間的關系,然而,現(xiàn)實生活中,旅客之間是存在相互影響的.社會網(wǎng)絡研究在于考慮每個節(jié)點價值的同時也把節(jié)點間的聯(lián)系進行量化.本文主要是利用社會網(wǎng)絡的相關知識,分析旅客間內(nèi)在關系,構建民航旅客社會網(wǎng)絡并挖掘出有價值的旅客,為企業(yè)市場營銷提供決策支持,有利于民航企業(yè)提高服務質量,同時旅客也因此獲得更具針對性的優(yōu)質的航空服務.首先本文提出了一種基于PNR數(shù)據(jù)間關系,構建民航旅客社會網(wǎng)絡的方法,并且利用某航空公司多條航線上的旅客出行記錄進行實驗,提取出了網(wǎng)絡中最大的連通子圖,為進一步研究網(wǎng)絡節(jié)點的價值(重要節(jié)點)提供有利的實驗基礎.其次為了更精確查找網(wǎng)絡中有價值的節(jié)點(重要節(jié)點),在研究與比較了多種模型的基礎上,本文提出了一種基于多層次灰色關聯(lián)分析的民航旅客社會網(wǎng)絡價值發(fā)現(xiàn)模型.考慮到普通聚類系數(shù)不能衡量聚類的規(guī)模,提出了修正的聚類系數(shù);建立多層次-灰色關聯(lián)分析模型,實現(xiàn)對網(wǎng)絡節(jié)點的排序.把該模型應用在民航旅客社會網(wǎng)絡中,得到了理想的結果,通過與實際情況對比,進一步驗證了模型的可靠性.最后本文提出基于重要節(jié)點發(fā)現(xiàn)算法的民航旅客社會網(wǎng)絡價值模型,主要是研究了系統(tǒng)科學,網(wǎng)絡關系和互聯(lián)網(wǎng)搜索這三個領域中的四種代表算法,并采用F-度量的方法對計算結果進行比較,篩選出重要的節(jié)點,通過度,二重度,點權,二重點權指標對節(jié)點的可靠性進行分析,找出了每個連通子圖中的重要節(jié)點.綜上所述,本文主要構建基于PNR數(shù)據(jù)的民航旅客社會網(wǎng)絡,提出基于多層次灰色關聯(lián)分析模型與基于重要節(jié)點發(fā)現(xiàn)算法的民航旅客社會網(wǎng)絡價值模型,模型仿真的應用表明,可以發(fā)現(xiàn)有價值的旅客,為航空公司的決策提供幫助,通過對高價值旅客的專門營銷,實現(xiàn)以最小代價達到最大利益,從而為航空公司節(jié)約成本.
[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.
【學位授予單位】：中國民航大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：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.
【學位授予單位】：中國民航大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：V354;TP393.09
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