Abstract—The development of travel industry gradually
fosters personalized requirements of tourists, such as setting the
start place, exploiting interesting activities and organizing the
travel route. In this paper, we take advantage of two online
websites to collect information of both scenic spots and
real-world local activities, and we proposed three rule-based
methods to recommend travel routes for tourists, which can
take their instant location into account and satisfy their
personalized demands. Specifically, we extract scenery spots
dataset from Flickr and popular activities from Douban-Event
in line with the visiting city and date. Then we process these
items and take the filtering results as the recommendation
candidates. Finally based on popularity and geographical
location of these venues/activities, we focus on arranging a
colorful travel route, which covers not only the everlasting
scenic spots, but also some temporary activities. We evaluate
the quality of travel routes produced by our recommendation
approaches with an alternative plan suggested by a professional
travel site. The results justify the advantages of our approaches
over the baseline method provided by travel experts.
Index Terms—DoubanEvent, flickr, popularity, travel route.
Jie Li, Yujiu Yang, and Wenhuang Liu are with Graduate School at
Shenzhen, Tsinghua University, China (e-mail: jli11@tsinghua.edu.cn,
yang.yujiu@sz.tsinghua.edu.cn, lwh@sz.tsinghua.edu.cn).
[PDF]
Cite: Jie Li, Yujiu Yang, and Wenhuang Liu, "Exploring Personalized Travel Route Using POIs," International Journal of Computer Theory and Engineering vol. 7, no. 2, pp. 126-131, 2015.
