Trip recommendation with multiple user constraints by integrating point-of-interests and travel packages

Shih Hsin Fang, Eric Hsueh Chan Lu, Vincent S. Tseng

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

12 Citations (Scopus)

Abstract

With the advances of mobile communication techniques in recent years, numerous kinds of Location-Based Services (LBSs) have been developed and one popular application of LBSs is trip recommendation. Although there exist already a number of studies on this topic in literatures, most of them focused on combining a set of point-of-interests (POIs, or say attractions) as a trip based on user-specific constraints. In another way, some few works discussed making recommendation in terms of travel packages, which have the benefits of lower cost and higher convenience. However, no prior work explores to integrate attractions and travel packages simultaneously for trip recommendation. In fact, such a hybrid-style recommender can provide higher benefits for users although there exist critical challenges here like the efficiency issue in such kind of real-time applications. In this paper, we propose a novel framework named Package-Attraction-based Trip Recommender (PATR) to efficiently recommend the personalized trips satisfying multiple constraints by effectively combining attractions and packages. In PATR, a Score Inference Model is proposed to infer the scores of attractions and packages by taking user-based preference and temporal-based properties into account. Then, the Hybrid Trip-Mine algorithm is proposed to efficiently discover the optimal trip which satisfies the multiple user-specific constraints with both of attractions and packages considered simultaneously. Furthermore, we propose two pruning strategies based on Hybrid Trip-Mine, named Score Estimation (SE) and Score Bound Tightening (SBT), to further improve the execution efficiency and memory utilization. To the best of our knowledge, this is the first work on travel recommendation that considers attractions and packages simultaneously. Through extensive experimental evaluations, our proposed approaches were shown to deliver excellent performance.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE 15th International Conference on Mobile Data Management, IEEE MDM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages33-42
Number of pages10
ISBN (Electronic)9781479957057
DOIs
Publication statusPublished - 2014 Oct 5
Event15th IEEE International Conference on Mobile Data Management, IEEE MDM 2014 - Brisbane, Australia
Duration: 2014 Jul 152014 Jul 18

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
Volume1
ISSN (Print)1551-6245

Other

Other15th IEEE International Conference on Mobile Data Management, IEEE MDM 2014
Country/TerritoryAustralia
CityBrisbane
Period14-07-1514-07-18

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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