分布式聚类算法在航空客票代理人细分中的应用
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摘要
为了快速分析航空客票代理人在机票销售市场中所扮演的角色,为不同类型的代理人制定相应的合作与销售方案,针对传统分类方法主观性过强以及集中式系统框架难以进行海量数据聚类分析的问题,提出分布式Canopy-K-means算法对航空客票代理人销售数据进行聚类,并将聚类结果结合市场实际情况进行推测,得到代理人在市场中的角色。结果表明,聚类结果与相关代理人的考核结果相符合,具有实际意义,可为航空公司的代理人管理提供参考。
In order to rapidly analyze the role of airline agents in ticket sales market and make corresponding cooperation plan as well as sales plan for different types of agents, aiming at the subjectivity of traditional classification methods and the difficulty of centralized system framework in massive data clustering and analyses, distributed Canopy-K-means algorithm is proposed in airline agents clustering, combining clustering results with actual market situation to obtain the agent's role in market. Experimental results show that the final clustering result is in line with the actual evaluation results of relevant agents, and has practical significance. Finally, according to the clustering results, feasible suggestions for airlines are provided, helping airlines to manage sales agents.
In order to rapidly analyze the role of airline agents in ticket sales market and make corresponding cooperation plan as well as sales plan for different types of agents, aiming at the subjectivity of traditional classification methods and the difficulty of centralized system framework in massive data clustering and analyses, distributed Canopy-K-means algorithm is proposed in airline agents clustering, combining clustering results with actual market situation to obtain the agent's role in market. Experimental results show that the final clustering result is in line with the actual evaluation results of relevant agents, and has practical significance. Finally, according to the clustering results, feasible suggestions for airlines are provided, helping airlines to manage sales agents.
引文
[1]张丽,丁晓东,孙占芳.航空客票销售渠道的博弈研究[J].数学的实践与认识, 2014, 44(19):155-161.
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[7]江小平,李成华,向文,等. k-means聚类算法的MapReduce并行化实现[J].华中科技大学学报(自然科学版), 2011, 39(s1):120-124.
[8]贾瑞玉,管玉勇,李亚龙.基于MapReduce模型的并行遗传kmeans聚类算法[J].计算机工程与设计, 2014, 35(2):657-660.
[9] YANG YANG, RUTAYISIRE T, LIN CHAO, et al. An improved CopKmeans clustering for solving constraint violation based on MapReduce framework[J]. Fundamenta Informaticae, 2013, 126(4):301-318.
[10]周晨烨.浅谈航空客运代理销售模式与管理对策[J].空运商务,2014(348):15-18.
[2]潘玲玲,张育平,徐涛.核DBSCAN算法在民航客户细分中的应用[J].计算机工程, 2012, 38(10):70-73.
[3]冯霞,徐冰宇,卢敏.民航旅客订票行为细分及群体特征分析[J].计算机工程与设计, 2015, 36(8):2217-2222.
[4]石磊,陈伟.基于大数据的航班调度优化模型与算法初探[J].智能计算机与应用, 2016, 6(2):84-86.
[5] CHU CHENGTAO, SANG K K, LIN YIAN, et al. Map-reduce for machine learning on multicore[C]//20th Annual conference on Neural Information Processing Systems, Vancouver, Dec 4-7, 2006, 19:281-288.
[6]谢雪莲,李兰友.基于云计算的并行K-means聚类算法研究[J].计算机测量与控制, 2014, 22(5):1510-1512.
[7]江小平,李成华,向文,等. k-means聚类算法的MapReduce并行化实现[J].华中科技大学学报(自然科学版), 2011, 39(s1):120-124.
[8]贾瑞玉,管玉勇,李亚龙.基于MapReduce模型的并行遗传kmeans聚类算法[J].计算机工程与设计, 2014, 35(2):657-660.
[9] YANG YANG, RUTAYISIRE T, LIN CHAO, et al. An improved CopKmeans clustering for solving constraint violation based on MapReduce framework[J]. Fundamenta Informaticae, 2013, 126(4):301-318.
[10]周晨烨.浅谈航空客运代理销售模式与管理对策[J].空运商务,2014(348):15-18.