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ISPRS Int. J. Geo-Inf. 2018, 7(2), 67; https://doi.org/10.3390/ijgi7020067

An Automatic User Grouping Model for a Group Recommender System in Location-Based Social Networks

Department of Geospatial Information Systems, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19967 15433, Iran
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Received: 29 December 2017 / Revised: 10 February 2018 / Accepted: 18 February 2018 / Published: 21 February 2018
(This article belongs to the Special Issue Geoinformatics in Citizen Science)
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Abstract

Spatial group recommendation refers to suggesting places to a given set of users. In a group recommender system, members of a group should have similar preferences in order to increase the level of satisfaction. Location-based social networks (LBSNs) provide rich content, such as user interactions and location/event descriptions, which can be leveraged for group recommendations. In this paper, an automatic user grouping model is introduced that obtains information about users and their preferences through an LBSN. The preferences of the users, proximity of the places the users have visited in terms of spatial range, users’ free days, and the social relationships among users are extracted automatically from location histories and users’ profiles in the LBSN. These factors are combined to determine the similarities among users. The users are partitioned into groups based on these similarities. Group size is the key to coordinating group members and enhancing their satisfaction. Therefore, a modified k-medoids method is developed to cluster users into groups with specific sizes. To evaluate the efficiency of the proposed method, its mean intra-cluster distance and its distribution of cluster sizes are compared to those of general clustering algorithms. The results reveal that the proposed method compares favourably with general clustering approaches, such as k-medoids and spectral clustering, in separating users into groups of a specific size with a lower mean intra-cluster distance. View Full-Text
Keywords: location-based social networks (LBSNs); clustering; user preference; social relationship effect; spatial proximity location-based social networks (LBSNs); clustering; user preference; social relationship effect; spatial proximity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Khazaei, E.; Alimohammadi, A. An Automatic User Grouping Model for a Group Recommender System in Location-Based Social Networks. ISPRS Int. J. Geo-Inf. 2018, 7, 67.

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