GeoLife2.0 is a GPS-data-driven social networking service where people can share life experiences and connect to each other with their location histories. By mining people\u2019s location history, GeoLife can measure the similarity between users and perform personalized friend recommendation for an individual. Later, we can predict the individual\u2019s interest level in the locations visited by their friends while have not been found by them. The locations with relatively high interesting level can be recommended. Therefore, GeoLife2.0 can expand a user\u2019s social network, provide them with a trustworthy resource matching their interests and help them sponsor geo-related activities like cycling with minimal effort.<\/p>\n","protected":false},"excerpt":{"rendered":"
GeoLife2.0 is a GPS-data-driven social networking service where people can share life experiences and connect to each other with their location histories. By mining people\u2019s location history, GeoLife can measure the similarity between users and perform personalized friend recommendation for an individual. Later, we can predict the individual\u2019s interest level in the locations visited by […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":[{"type":"user_nicename","value":"yuzhen"},{"type":"user_nicename","value":"xingx"},{"type":"user_nicename","value":"wyma"}],"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"Proceedings of the 10th International Conference on Mobile Data Management (MDM 2009)","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"Copyright \u00a9 2007 IEEE. 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with Spatial Trajectories","post_name":"computing-with-spatial-trajectories","post_type":"msr-project","post_date":"2011-11-08 23:36:50","post_modified":"2017-06-06 09:31:37","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/computing-with-spatial-trajectories\/","post_excerpt":"Editor: Yu Zheng,\u00a0Xiaofang Zhou Foreword by Jiawei Han Editorial board: Ralf Hartmut G\u00fcting, Hans-Peter Kriegel, Hanan Samet [Order it on Amazon] [Buy it from Springer] [Preview this book (Outline and Preface)] With the rapid development of wireless communication and mobile computing technologies and global positioning and navigational systems, spatial trajectory data has been mounting up, calling for systematic research and development of new computing technologies for storage, preprocessing, retrieving, and mining of trajectory 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