Traveling path recommendation using temporal transit patterns

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

Abstract

In this work, we aim to collectively recommend traveling paths by leveraging the check-in data through mining the moving behaviors of users. We call such traveling paths as Temporal Transit Patterns (TTP), which capture the representative traveling behaviors over consecutive locations, from the big check-in data. To achieve such goal, we propose a novel Temporal Transit Pattern Mining method (TTPM-method), which devises an unsupervised mechanism that automatically summarizes the representative travel patterns us guarantee better time efficiency lower and memory usage. Based on the mined TTP, a novel system, TTP-Rec, is then developed. TTP-Rec not only allows users to specify starting/end locations, but also provides the flexibility of the time constraint requirement (i.e., the expected duration of the trip). Considering a sequence of check-in points as a traveling path, we mine the frequent sequences with a ranking mechanism to achieve the goal. Our TTPRec targets at travelers who are unfamiliar to the objective area/city and have time limitation in the trip.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014
PublisherThe AAAI Press
Pages648-649
Number of pages2
ISBN (Electronic)9781577356578
Publication statusPublished - 2014 Jan 1
Event8th International Conference on Weblogs and Social Media, ICWSM 2014 - Ann Arbor, United States
Duration: 2014 Jun 12014 Jun 4

Publication series

NameProceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014

Other

Other8th International Conference on Weblogs and Social Media, ICWSM 2014
CountryUnited States
CityAnn Arbor
Period14-06-0114-06-04

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Hsieh, H. P., & Li, C. T. (2014). Traveling path recommendation using temporal transit patterns. In Proceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014 (pp. 648-649). (Proceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014). The AAAI Press.