Abstract
Travel route recommendation can strongly influence users' satisfaction and the success of touristic businesses. This paper proposes a personalized travel recommendation algorithm with time planning. We use landmark categorization and region clustering to obtain effective elements. Then we build a travel map to generate all possible travel routes. Our proposed algorithm has higher precision in landmark recommendation and time planning than thoes in previous algorithms.
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE 7th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2017 |
| Publisher | IEEE Computer Society |
| Pages | 239-242 |
| Number of pages | 4 |
| Volume | 2017-September |
| ISBN (Electronic) | 9781509040148 |
| DOIs | |
| Publication status | Published - 2017 Dec 14 |
| Event | 7th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2017 - Berlin, Germany Duration: 2017 Sep 3 → 2017 Sep 6 |
Other
| Other | 7th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2017 |
|---|---|
| Country | Germany |
| City | Berlin |
| Period | 17/9/3 → 17/9/6 |
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Keywords
- landmark
- time planning
- travel route recommendation
- user preference
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Industrial and Manufacturing Engineering
- Media Technology
Cite this
Personalized one-day travel with multi-nearby-landmark recommendation. / Bao, Siya; Yanagisawa, Masao; Togawa, Nozomu.
2017 IEEE 7th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2017. Vol. 2017-September IEEE Computer Society, 2017. p. 239-242.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Personalized one-day travel with multi-nearby-landmark recommendation
AU - Bao, Siya
AU - Yanagisawa, Masao
AU - Togawa, Nozomu
PY - 2017/12/14
Y1 - 2017/12/14
N2 - Travel route recommendation can strongly influence users' satisfaction and the success of touristic businesses. This paper proposes a personalized travel recommendation algorithm with time planning. We use landmark categorization and region clustering to obtain effective elements. Then we build a travel map to generate all possible travel routes. Our proposed algorithm has higher precision in landmark recommendation and time planning than thoes in previous algorithms.
AB - Travel route recommendation can strongly influence users' satisfaction and the success of touristic businesses. This paper proposes a personalized travel recommendation algorithm with time planning. We use landmark categorization and region clustering to obtain effective elements. Then we build a travel map to generate all possible travel routes. Our proposed algorithm has higher precision in landmark recommendation and time planning than thoes in previous algorithms.
KW - landmark
KW - time planning
KW - travel route recommendation
KW - user preference
UR - http://www.scopus.com/inward/record.url?scp=85044002563&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044002563&partnerID=8YFLogxK
U2 - 10.1109/ICCE-Berlin.2017.8210637
DO - 10.1109/ICCE-Berlin.2017.8210637
M3 - Conference contribution
VL - 2017-September
SP - 239
EP - 242
BT - 2017 IEEE 7th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2017
PB - IEEE Computer Society
ER -