华东师范大学学报(自然科学版) ›› 2018, Vol. 2018 ›› Issue (2): 52-62.doi: 10.3969/j.issn.1000-5641.2018.02.006

• 计算机科学 • 上一篇    下一篇

一类多日均衡满意度的旅行规划算法

徐侃, 郑骏   

  1. 华东师范大学 计算机科学与软件工程学院, 上海 200062
  • 收稿日期:2017-01-23 出版日期:2018-03-25 发布日期:2018-03-22
  • 通讯作者: 郑骏,男,教授级高级工程师,博士生导师,研究方向为Web应用技术.E-mail:jzheng@cc.ecnu.edu.cn. E-mail:jzheng@cc.ecnu.edu.cn
  • 作者简介:徐侃,男,硕士研究生,研究方向为普适计算.E-mail:2540788463@qq.com.

Balancing travel satisfaction algorithm for multi-day trip planning

XU Kan, ZHENG Jun   

  1. School of Computer Science and Software Engineering, East China Normal University, Shanghai 200062, China
  • Received:2017-01-23 Online:2018-03-25 Published:2018-03-22

摘要: 基于位置的服务是确定移动用户所在位置并根据位置来提供的一种服务,其中,旅行规划是众多服务应用中的热点之一.通过基于位置的服务,人们可以根据自己的偏好制订不同的旅行规划.然而,在大多数研究中,旅行规划只关注于在所有兴趣点中制订一条符合旅行要求的路线.当游客决定在所在城市游玩多日时,这些研究所制订的路线给游客所带来的旅行满意度就会逐天递减,不符合多日旅程线路规划的制订.为了提高游客旅行时多日旅行满意度的稳定性问题,将天数因素作为多日旅行规划的参数之一,通过获取兴趣点集合的相关信息,如位置、评分、类别等,构建兴趣点网络模型,利用启发式算法得出最佳的路线,制订有效的多日旅行规划.实验结果证明,所提出的算法可以高效地得到多条旅行均衡的高质量旅行路线.

关键词: 多日旅行规划, 基于位置服务, 普适计算

Abstract: Location-based service is a kind of service that obtains the location of mobile user and provides it according to location. Among them, one of the active topics is trip planning. People can make different trip planning to meet their multiple requirements by location-based service. However, in most studies, trip planning only focus on searching one route in many locations according to user's demands. When people are trying to visit the city more than one day, the travel satisfaction of the routes provided by previous researches would reduce by day. Hence, the previous work cannot meet the requirement of multi-day trip planning. To improve the satisfaction stability of multi-day trip planning, we use trip day as one of the multi-day travel planning parameters. We acquire points of interest (POIs) information (e.g., location, scoring, category, etc.) and construct a POI network model, obtain optimal trip routes through heuristic algorithm, develop an effective multi-day travel planning. The experimental results demonstrate that our proposed method can plan a multi-day trip with high quality and more balanced route.

Key words: multi-day trip planning, location-based service, ubiquitous computing

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