TripCloud: An intelligent cloud-based trip recommendation system

Josh Jia Ching Ying, Eric Hsueh Chan Lu, Bo Nian Shi, Vincent S. Tseng

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

5 Citations (Scopus)


With the advance of Location-Based Services (LBS), researches on trip recommendation have attracted extensive attentions. Among them, one active topic is trip planning. In the previous studies on trip planning, various user constraints such as travel time, travel budget, attraction categories, etc., have been considered and users' past travel logs were analyzed for travel recommendation. However, such kind of trip planning approaches cause the computational complexity to increase significantly. Hence, in this paper, we demonstrate a cloud-based travel recommendation system named TripCloud, which is built by extending our previous work, Personalized Trip Recommendation (PTR), for meeting user's multiple constraints with efficient trip planning. TripCloud encapsulates several data mining techniques and a cloud-based trip planning model to rate the interestingness of each attraction and plan an interesting trip, respectively. Visualization interface is also provided to exhibit the recommended trips based on the characteristics of user constraints.

Original languageEnglish
Title of host publicationAdvances in Spatial and Temporal Databases - 13th International Symposium, SSTD 2013, Proceedings
Number of pages6
Publication statusPublished - 2013 Aug 13
Event13th International Symposium on Spatial and Temporal Databases, SSTD 2013 - Munich, Germany
Duration: 2013 Aug 212013 Aug 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8098 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other13th International Symposium on Spatial and Temporal Databases, SSTD 2013

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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