{"id":159481,"date":"2010-06-01T00:00:00","date_gmt":"2010-06-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/geolife-a-collaborative-social-networking-service-among-user-location-and-trajectory\/"},"modified":"2018-10-16T21:28:06","modified_gmt":"2018-10-17T04:28:06","slug":"geolife-a-collaborative-social-networking-service-among-user-location-and-trajectory","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/geolife-a-collaborative-social-networking-service-among-user-location-and-trajectory\/","title":{"rendered":"GeoLife: A Collaborative Social Networking Service among User, location and trajectory"},"content":{"rendered":"<div class=\"asset-content\">\n<p>People travel in the real world and leave their location history in a form of trajectories. These trajectories do not only connect locations in the physical world but also bridge the gap between people and locations. This paper introduces a social networking service, called GeoLife, which aims to understand trajectories, locations and users, and mine the correlation between users and locations in terms of user-generated GPS trajectories. GeoLife offers three key applications scenarios: 1) sharing life experiences based on GPS trajectories; 2) generic travel recommendations, e.g., the top interesting locations, travel sequences among locations and travel experts in a given region; and 3) personalized friend and location recommendation.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>People travel in the real world and leave their location history in a form of trajectories. These trajectories do not only connect locations in the physical world but also bridge the gap between people and locations. This paper introduces a social networking service, called GeoLife, which aims to understand trajectories, locations and users, and mine [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13554,13555],"msr-publication-type":[193715],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-159481","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-computer-interaction","msr-research-area-search-information-retrieval","msr-locale-en_us"],"msr_publishername":"IEEE","msr_edition":"IEEE Data(base) Engineering 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