Abstract
Location-based services allow users to perform geo-spatial recording actions, which facilitates the mining of the moving activities of human beings. This paper proposes a system, Trip Router, to recommend time-sensitive trip routes consisting of a sequence of locations with associated time stamps based on knowledge extracted from large-scale location check-in data. We first propose a statistical route goodness measure considering: (a) the popularity of places, (b) the visiting order of places, (c) the proper visiting time of each place, and (d) the proper transit time from one place to another. Then we construct the time-sensitive route recommender with two major functions: (1) constructing the route based on the user-specified source location with the starting time, (2) composing the route between the specified source location and the destination location given a starting time. We devise a search method, Guidance Search, to derive the routes efficiently and effectively. Experiments on Gowalla check-in datasets with user study show the promising performance of our Trip Router system.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014 |
| Editors | Zhi-Hua Zhou, Wei Wang, Ravi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, Xindong Wu |
| Publisher | IEEE Computer Society |
| Pages | 1207-1210 |
| Number of pages | 4 |
| Edition | January |
| ISBN (Electronic) | 9781479942749 |
| DOIs | |
| Publication status | Published - 2015 Jan 26 |
| Event | 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014 - Shenzhen, China Duration: 2014 Dec 14 → … |
Publication series
| Name | IEEE International Conference on Data Mining Workshops, ICDMW |
|---|---|
| Number | January |
| Volume | 2015-January |
| ISSN (Print) | 2375-9232 |
| ISSN (Electronic) | 2375-9259 |
Other
| Other | 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014 |
|---|---|
| Country | China |
| City | Shenzhen |
| Period | 14-12-14 → … |
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Software
Cite this
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Trip router : A time-sensitive route recommender system. / Hsieh, Hsun-Ping; Li, Cheng-Te; Lin, Shou De.
Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014. ed. / Zhi-Hua Zhou; Wei Wang; Ravi Kumar; Hannu Toivonen; Jian Pei; Joshua Zhexue Huang; Xindong Wu. January. ed. IEEE Computer Society, 2015. p. 1207-1210 7022735 (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 2015-January, No. January).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Trip router
T2 - A time-sensitive route recommender system
AU - Hsieh, Hsun-Ping
AU - Li, Cheng-Te
AU - Lin, Shou De
PY - 2015/1/26
Y1 - 2015/1/26
N2 - Location-based services allow users to perform geo-spatial recording actions, which facilitates the mining of the moving activities of human beings. This paper proposes a system, Trip Router, to recommend time-sensitive trip routes consisting of a sequence of locations with associated time stamps based on knowledge extracted from large-scale location check-in data. We first propose a statistical route goodness measure considering: (a) the popularity of places, (b) the visiting order of places, (c) the proper visiting time of each place, and (d) the proper transit time from one place to another. Then we construct the time-sensitive route recommender with two major functions: (1) constructing the route based on the user-specified source location with the starting time, (2) composing the route between the specified source location and the destination location given a starting time. We devise a search method, Guidance Search, to derive the routes efficiently and effectively. Experiments on Gowalla check-in datasets with user study show the promising performance of our Trip Router system.
AB - Location-based services allow users to perform geo-spatial recording actions, which facilitates the mining of the moving activities of human beings. This paper proposes a system, Trip Router, to recommend time-sensitive trip routes consisting of a sequence of locations with associated time stamps based on knowledge extracted from large-scale location check-in data. We first propose a statistical route goodness measure considering: (a) the popularity of places, (b) the visiting order of places, (c) the proper visiting time of each place, and (d) the proper transit time from one place to another. Then we construct the time-sensitive route recommender with two major functions: (1) constructing the route based on the user-specified source location with the starting time, (2) composing the route between the specified source location and the destination location given a starting time. We devise a search method, Guidance Search, to derive the routes efficiently and effectively. Experiments on Gowalla check-in datasets with user study show the promising performance of our Trip Router system.
UR - http://www.scopus.com/inward/record.url?scp=84936870296&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84936870296&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2014.34
DO - 10.1109/ICDMW.2014.34
M3 - Conference contribution
AN - SCOPUS:84936870296
T3 - IEEE International Conference on Data Mining Workshops, ICDMW
SP - 1207
EP - 1210
BT - Proceedings - 14th IEEE International Conference on Data Mining Workshops, ICDMW 2014
A2 - Zhou, Zhi-Hua
A2 - Wang, Wei
A2 - Kumar, Ravi
A2 - Toivonen, Hannu
A2 - Pei, Jian
A2 - Zhexue Huang, Joshua
A2 - Wu, Xindong
PB - IEEE Computer Society
ER -