Recommending friends and locations over a heterogeneous spatio-temporal graph
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Recommender systems in location-based social networks (LBSNs), such as Facebook Places and Foursquare, have focused on recommending friends or locations to registered users by combining information derived from explicit (i.e. friendship network) and implicit (i.e. user-item rating network, user-location network, etc.) subnetworks. However, previous’s work models were static, failing to capture adequately user preferences as they change over time. In this paper, we provide a novel recommendation method by incorporating the time dimension into our model through an auxiliary artificial node (i.e. session). In particular, we construct a hybrid tripartite (i.e., user, location, session) graph, which incorporates 7 different unipartite and bipartite graphs. Then, we run on it the well known Random Walk with Restart (RWR) algorithm, which randomly propagate through the network structure which has 7 differently weighted edge types (i.e., user-location, user-session, user-user, etc.) among its entities. We evaluate experimentally how RWR improve the procession of the recommendations during different time-windows against one state-of-the-art algorithm over the GeoSocialRec and the Foursquare datasets.
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Proceedings of the Workshop on Location-Aware Recommendations (LocalRec 2015) co-located with the 9th ACM Conference on Recommender Systems (RecSys 2015) Bouros, P; Lathia, N; Renz, M; Ricci, F; Sacharidis, D (CEUR, 2015)
Bouros, P; Lathia, N; Renz, M; Ricci, F; Sacharidis, D (ACM, 2015)The amount of available geo-referenced data has seen a dramatic explosion over the past few years. Human activities now generate digital traces that are annotated with location data, enabling the collection of rich information ...
Sattari M; Toroslu I; Karagoz P; Symeonidis P; Manolopoulos Y (Springer-Verlag London Ltd, 2015)With the increasing availability of location-based services, location-based social networks and smart phones, standard rating schema of recommender systems that involve user and item dimensions is extended to three-dimensional ...