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Social networks have become an everyday activity in people’s life, people now can communicate, share their day life activities with their family and friends using online social media (OSN) applications and in consequence Social Networking became a very wide and rich topic for research and analysis for businesses and researchers in different fields .
[Tork, Hadi Fanaee. "Spatio-temporal clustering methods classification." ]
two dimensions of time and space which embed patterns in data
One of the pioneers in the field of Location-Based Social Networks is Foursquare. Foursquare is a platform that was launched in 2009 and now it has around 60 million users.
In a time of 2 years Foursquare was named Best Location-Based Service in the TechCrunch Crunchies and named a Technology Pioneer by the World Economic Forum in the Information Technologies and New Media category according to Wikipedia’s page on Foursquare.
Our motive in this seminar is to combine frequent and sequential pattern mining with clustering techniques to be able to construct a solid ground of analysis on foursquare dataset that can be later injected in recommender system engines to improve quality of recommendations for users and businesses.
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