Computer Science ›› 2017, Vol. 44 ›› Issue (6): 199-205.doi: 10.11896/j.issn.1002-137X.2017.06.033

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Group Travel Trip Recommendation Method in LBSNs

LI Xiao-lun and DING Zhi-jun   

  • Online:2018-11-13 Published:2018-11-13

Abstract: With the widespread adoption of GPS-enabled devices,such as smartphone,GPS navigation device,GPS logger,etc.,more and more location information is collected.Recommender systems for location-based social networks (LBSNs) have received more attention.The research on recommending a trip to a group is a hot topic,but most related works mainly focus on recommending trip to a user and lack in recommending trip to a group.Therefore,this paper proposed a trip recommender method for a group in LBSNs.First,according to user’s check-ins,the proposed method uses K-means and spectral clustering to mine groups who have a great many same check-ins.Then,group’s preference is obtained based on their common check-ins.At last, combining group’s time and cost constraint,a trip recommender algorithm is designed to recommend trip which satisfies group’s preference to a group.This paper conducted experiments with users’ real check-ins of Sina weibo.The experimental results show that the proposed method in this paper to recommend trips to a group achieves good effects.

Key words: Group,Travel trip,LBSNs,Spectral clustering,K-means,Recommender system

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