Constructing trip routes with user preference from location check-in data

Authors:
Hsun-Ping Hsieh;Cheng-Te Li
Affiliations:
National Taiwan University, Taipei, Taiwan Roc;National Taiwan University, Taipei, Taiwan Roc
Venue:
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Year:
2013

Citing 7
Cited 0

Searching trajectories by locations: an efficiency study

Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Discovering popular routes from trajectories

ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Cost-aware travel tour recommendation

Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Personalized Travel Package Recommendation

ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
Constructing popular routes from uncertain trajectories

Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting large-scale check-in data to recommend time-sensitive routes

Proceedings of the ACM SIGKDD International Workshop on Urban Computing
Location-based and preference-aware recommendation using sparse geo-social networking data

Proceedings of the 20th International Conference on Advances in Geographic Information Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a novel trip route construction using location check-in data. Given a set of preference lists of locations from users, we aim to coordinate their preferred locations to visit and construct a route which not only satisfying user preferences as many as possible, but also being popular and reasonable. We formulate such preferred route construction as an optimization problem. We solve it efficiently and effectively by devising some greedy methods. Experiments on Gowalla large-scale check-in data show the promising effectiveness and efficiency of our methods.