Simulation framework for travel trajectory generation and mobile transaction modeling

E. H. Lu, J. Ying, Huan-Sheng Chen, K. Lin, V. Tseng, Huan-Wen Tsai, K. H. Cheng, Shun-Chieh Lin
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引用次数: 2

Abstract

In recent years, Location-Based Services (LBSs) have received a lot of attentions due to a wide range of potential applications. In such mobile applications and services, the travel recommendation system is one of popular LBSs for mobile users. More and more research studies focus on discovering of various kinds of mobile patterns from various mobile databases. In which, one of popular research issues is mining of the travel trajectory patterns from mobile travel trajectory databases. Mining travel knowledge from travel trajectory data benefits for supporting of an intelligent travel recommendation system. However, it is not easy to obtain the real travel trajectory data for mobile users since the problem of personal privacy. To develop a travel trajectory data generator is very useful for the research communities on mobile travel behavior mining. In this paper, we present a simulation framework to generate mobile travel trajectory data based on the statistics and observations of real travel information. In the simulation model, we generate not only the travel trajectories for mobile users but also the mobile transactions for each arrived attraction according to the reasonable probability designs.
出行轨迹生成与移动事务建模仿真框架
近年来,基于位置的服务(lbs)因其广泛的应用前景受到了广泛的关注。在这些移动应用和服务中,旅游推荐系统是移动用户最常用的lbs之一。越来越多的研究集中在从各种移动数据库中发现各种移动模式上。其中,从移动出行轨迹数据库中挖掘出行轨迹模式是研究热点之一。从旅行轨迹数据中挖掘旅行知识有利于支持智能旅行推荐系统。然而,由于个人隐私问题,获取移动用户真实的出行轨迹数据并不容易。开发移动出行轨迹数据生成器对于移动出行行为挖掘的研究具有重要意义。在本文中,我们提出了一个基于真实出行信息统计和观测的模拟框架来生成移动出行轨迹数据。在仿真模型中,我们不仅生成了移动用户的出行轨迹,还根据合理的概率设计生成了每个到达景点的移动交易。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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