期刊文献+

改进二部分图的民航旅客出行偏好模式的构建

CONSTRUCTING AVIATION PASSENGER TRAVEL PREFERENCES PATTERN WITH IMPROVED BIPARTITE GRAPH
下载PDF
导出
摘要 根据旅客的个人信息、历史购买信息、常旅客信息以及旅客通过终端设备的历史访问记录,实现自动的旅客出行偏好模式的构建。根据原始的二部分图资源分配算法提出一种对资源分配矩阵的改进方法,并且与原始矩阵进行耦合,以提高推荐的精确度。实验结果表明该改进方法的精确度随着可变参数的变化而变化,当可变参数取某一最优化值时,改进后的方法精确度优于改进前的。将改进后的方法用于构建旅客出行偏好模式,应用后的结果与原始数据集比较,的确发现了旅客出行的规律。 According to passenger's personal information, purchase history information, frequent flyer information and historical access re- cords of guests passing the terminal equipments, the automatic construction of passenger travel preferences pattern is realised. According to raw bipartite graph resource allocation algorithm we propose an improved approach for resources allocation matrix, and couple it with the origi- nal matrix to improve recommendation accuracy. Experimental results show that the accuracy of this improved method varies along with the changes of variable parameters, when the variable parameter is assigned a certain optimisation value, the accuracy of the improved method is superior to the one not improved. Applying the improved method to constructing the preference pattern of passenger travel, it does find the passenger travel rules by comparing the applied results with the original data set.
出处 《计算机应用与软件》 CSCD 2015年第2期81-84,共4页 Computer Applications and Software
基金 民航科技项目(MHRDZ201206)
关键词 改进二部分图 旅客出行 偏好模式 Improved bipartite graph Passenger travel Preferences pattern
  • 相关文献

参考文献10

二级参考文献147

  • 1徐凤亚,罗振声.文本自动分类中特征权重算法的改进研究[J].计算机工程与应用,2005,41(1):181-184. 被引量:56
  • 2全海金,邱玉辉,李瑞.基于用户行为及语义相关实时更新用户兴趣的推荐系统[J].计算机科学,2005,32(3):76-78. 被引量:5
  • 3王煜,周立柱,邢春晓.视频语义模型及评价准则[J].计算机学报,2007,30(3):337-351. 被引量:15
  • 4盖亮,冯志勇.集成语义信息的电子商务推荐系统[J].计算机工程与应用,2007,43(11):197-200. 被引量:4
  • 5Resnick P, lakovou N, Sushak M, et al. GroupLens: An open architecture for collaborative filtering of netnews. Proc 1994 Computer Supported Cooperative Work Conf, Chapel Hill, 1994: 175-186
  • 6Hill W, Stead L, Rosenstein M, et al. Recommending and evaluating choices in a virtual community of use. Proc Conf Human Factors in Computing Systems. Denver, 1995:194 -201
  • 7梅田望夫.网络巨变元年-你必须参加的大未来.先觉:先觉出版社,2006
  • 8Adomavicius G, Tuzhilin A. Expert-driven validation of Rule Based User Models in personalization applications. Data Mining and Knowledge Discovery, 2001, 5(1-2):33-58
  • 9Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: A survey of the state-of-the art and possible extensions. IEEE Trans on Knowledge and Data Engineering, 2005, 17(6): 734-749
  • 10Rich E. User modeling via stereotypes. Cognitive Science, 1979, 3(4) : 329-354

共引文献461

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部