Time-slot-based point of interest recommendation on location-based social network
by Jun Zeng; Yinghua Li; Feng Li; Xin He; Junhao Wen
International Journal of Internet Manufacturing and Services (IJIMS), Vol. 5, No. 2/3, 2018

Abstract: Point-of-interest (POI) recommendation on location-based social network (LBSN) is an important service in mobile environment. POI recommendation recommends places that users have not visited before. In this paper, we introduce time slot to describe the feature vector of locations. We consider that the locations that user has visited may reflect user's preference. Hence, we calculate the similarity between the visited locations and the unvisited locations. Meanwhile, we consider the influence of the physical distance and the weight of the visited locations. We conduct an experiment and the experimental results show that our method has better precision and recall than the other two methods.

Online publication date: Thu, 24-May-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Internet Manufacturing and Services (IJIMS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com