Multiple days trip recommendation based on check-in data

Heng Ching Liao, Yi Chung Chen, Chiang Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution


A travel recommender system can generate suggested itineraries for users based on their preferences. However, current systems are not capable of simultaneously considering trip length, distance, user requirements and preferences when making recommendations, being only equipped to consider one or two of these variables at one time. Also, to generate recommendations the system must process all attractions in the database, requiring more data access and longer processing time. We analyzed the check-in records of users and utilized a new concept of time intervals combined with a multiple days trip algorithm to produce itineraries compatible with the interests and needs of users. By applying R-tree to the travel recommender system, we reduced data access times and computation time. Lastly, we propose a trip evaluator equation that can be used to compare the strengths and weaknesses of each algorithm. Experimental results verified the effectiveness of our method.

Original languageEnglish
Title of host publicationMultidisciplinary Social Networks Research - 2nd International Conference, MISNC 2015, Proceedings
EditorsKai Wang, Shiro Uesugi, Leon Wang, Koji Okuhara, I-Hsien Ting
PublisherSpringer Verlag
Number of pages15
ISBN (Print)9783662483183
Publication statusPublished - 2015
Event2nd International Conference on Multidisciplinary Social Networks Research, MISNC 2015 - Matsuyama, Japan
Duration: 2015 Sept 12015 Sept 3

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929


Other2nd International Conference on Multidisciplinary Social Networks Research, MISNC 2015

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)


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