6 datasets found

Location prediction forecasts a user’s location based on historical user mobility traces. To tackle the intrinsic sparsity issue of real-world user mobility traces,...

The dataset used in the paper is MovieLens-1M, Foursquare, and Yelp2018. These datasets are used for top-k recommendation task.

The dataset used in the paper is Twitter and Foursquare, two real-world aligned heterogeneous social networks.

The CA dataset is a collection of 483,813 check-ins made in Foursquare by 4,163 users living in California.

The SIN dataset is a collection of 194,108 check-ins made within Singapore from 2,321 users at 5,596 POIs between Aug. 2010 and Jul. 2011.

The Foursquare and Weeplace datasets contain users' check-in histories in the cities of New York, Los Angeles, and Chicago.