Data for: A Location-Based Orientation-Aware Recommender System Using IoT Smart Devices and Social Networks
datasetposted on 28.02.2020 by Soroush Ojagh, Mohammad Reza Malek, Steve Liang, Sara Saeedi
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
In this study, 20 recommendation lists are provided for each of 7,214 user's locations in total. Four different buffer sizes (two, five, ten, and 15 km) and four UPDs are considered for each user's location to prepare the event recommendation lists. In the implemented scenario, three different scenarios were applied in order to support research claims. The word "SC" refers to a specific scenario as "SC_1" refers to the first scenario. Totally, considering four circle buffers and four UPDs in each buffer, 16 buffer lines will be prepared as "sc_1_line_1" refers to the first UPD in the buffer size of two kilometers. In addition, "sc_1_cycle" refers to all the event venues that are located in the circle buffer size of two kilometers. "EventVenues" and "venuesMBBs" contain geospatial information for the selected venues and also their extracted minimum bounding boxes. All the imported building located in the city of Calgary, Alberta is in the "calgaryBuilding" table, and "userLocations" shows the spatial information considered for the 7,214 user's locations.