LBSN-based personalized routes recommendation

Li Chao Zhu, Zhi Jun Li, Shou Xu Jiang

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

2 Scopus citations

Abstract

In this paper, we present personalized routes recommendation on Location Based Social Network. We model user in both geographical space and semantic space, and define Activity Pattern to describe individual’s personalized character, i.e. individual’s activity regularity. We extract routes which match individual’s activity patterns from high similar users’ trajectories, and according to scoring strategy to recommend top-k routes to a user. We evaluated our method with a real GPS dataset collected from GeoLife. The results show that there exist Activity Pattern in individual’s movement, and our method is better than traditional Cosine-based Similarity method on both precisionand k-cover.

Original languageEnglish (US)
Title of host publicationMachine Tool Technology, Mechatronics and Information Engineering
EditorsZhongmin Wang, Liangyu Guo, Jianming Tan, Dongfang Yang, Dongfang Yang, Kun Yang, Dongfang Yang, Dongfang Yang, Dongfang Yang
PublisherTrans Tech Publications Ltd
Pages3230-3234
Number of pages5
ISBN (Electronic)9783038352464
DOIs
StatePublished - 2014
EventInternational Conference on Machine Tool Technology and Mechatronics Engineering, ICMTTME 2014 - Guilin, China
Duration: Jun 22 2014Jun 23 2014

Publication series

NameApplied Mechanics and Materials
Volume644-650
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Other

OtherInternational Conference on Machine Tool Technology and Mechatronics Engineering, ICMTTME 2014
CountryChina
CityGuilin
Period6/22/146/23/14

Keywords

  • Activity pattern
  • Location based social network
  • Routes recommendation

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