基于时间成本的旅游线路推荐方法研究

基于时间成本的旅游线路推荐方法研究(论文12000字)
摘要：旅游活动常常会受时间、空间、旅游支出等多种因素的影响，当旅游用户有个性化需求的时候，尤其是在旅游的时间花费上存在特殊的要求时，大部分旅游用户很难快速及时的确定出游路线。个人时空可达性就是研究在时空约束条件下旅游用户活动范围和活动路线问题。因此基于时间成本的旅游线路推荐问题可以转化为在考虑用户个人偏好的前提下去研究时空可达性问题，在满足用户的个性化需求的条件下，向用户推荐可达性优异的景点组合，并给出出行线路的规划问题。
本文基于个性化推荐算法，结合用户兴趣度、用户相似度和景点的流行度，提出了一种基于时间成本的旅游线路推荐算法，使用时空可达性来评价景点的可行性，并结合用户兴趣度和景点流行度，计算出一条或几条可达性好的景点组合供用户选择。
结果表明，该论文提出的推荐算法具有合理性和可行性，能够基本满足旅游用户在时间和景点类型方面的需求。
关键词：旅游线路推荐；个人时空可达性；兴趣度；流行度；个性化推荐算法

Research on the Method of Recommending Tour Line Based on Time Cost
Abstract：Tourism activities are often affected by many factors such as time, space, tourismspending, the influence of when traveling users with personalized needs, especially in tourismthere are special requirements on time, most of the tourism travel route users are difficult todetermine quickly and timely. Personalspatiotemporal accessibility is the study of the travel user activity scope and the activity route problem under the time-space constraints. So based on the time cost of travel to recommend problem can be converted into considering user preferences on the premise of research time and space accessibility problem, under the condition of meet the personalized needs of users, recommended to the user accessibility excellent attractions combination, and travel route planning problem is given.
In this paper, based on the personalized recommendation algorithm, combined with the user interest degree, the popularity of user similarity and attractions, this paper proposes a tourist route recommendation algorithm based on the time cost, use time and space accessibility to evaluate the feasibility of the scenic spots, and combined with the user interest and attractions popular degrees, calculate the accessibility of one or a few good spots combination for the user to choose from.
The results show that the proposed algorithm is reasonable and feasible, and can basically meet the needs of tourism users in time and scenic spot types.
Key words：Tourist route recommendation; personal space-time accessibility; interest; popularity; personalized recommendation algorithm

目录
1绪论    3
1.1研究背景、目的及意义    3
1.2国内外研究现状    3
1.3本文改进策略    3
1.4本文主要结构    4
2时空数据挖掘及相关问题    5
2.1时空数据的挖掘技术    5
2.2用户相似度    5
2.3数据的获取和预处理    6
2.3.2数据的预处理    6
2.4个性化推荐系统    6
3相关背景知识和问题描述    8
3.1景点区域分析    8
3.1.1带地理标签的照片    8
3.1.2停留点与景点区域    8
3.2个性化旅游推荐    9
3.2.1用户兴趣偏好推荐    9
3.2.2流行景点推荐    10
4 算法和具体实现    11
4.1景点区域分析和构建旅游景点数据库    11
4.2语义景点    11
4.3基于用户偏好和景点流行度的旅游推荐算法    12
4.4对传统相似度算法的改进及改进后的优缺点    14
5实验结果和分析    15
5.1算法参数实验及结果分析    15
5.1.1停留点算法检测中时间阈值和距离阈值的确定    15
5.1.2个性化推荐算法中权值的确定    15
5.2部分功能的实现和结果展示    17
6总结与展望    19
6.1总结    19
6.2展望    19
参考文献    19
致谢    22