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Seminar on Internet Technologies (Summer 2019): Difference between revisions
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Seminar on Internet Technologies (Summer 2019) (view source)
Revision as of 14:30, 29 May 2019
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| '''User Location Prediction based on Geo-social Networking Data (already assigned)''' | | '''User Location Prediction based on Geo-social Networking Data (already assigned to Hussain Nauman)''' | ||
| The increasing amount of user and location information in GSN makes the information overload phenomenon more and more serious. Although massive user generated data brings convenience to users' social and travel activities, it also causes certain trouble for their daily life. In this context, users are expecting smarter mobile applications, so that the location information can be employed to perceive their surrounding environment intelligently and further mine their behavior patterns in GSN, which ultimately provides personalized location-based services for users. Therefore, research on user location prediction comes into existence and have received extensive and in-depth attention from researchers. Through systematically analyzing the location data carried by user check-ins and comments, user location prediction can mine various user behavior patterns and their personal preferences, thus determining the visiting location of users in the future | | The increasing amount of user and location information in GSN makes the information overload phenomenon more and more serious. Although massive user generated data brings convenience to users' social and travel activities, it also causes certain trouble for their daily life. In this context, users are expecting smarter mobile applications, so that the location information can be employed to perceive their surrounding environment intelligently and further mine their behavior patterns in GSN, which ultimately provides personalized location-based services for users. Therefore, research on user location prediction comes into existence and have received extensive and in-depth attention from researchers. Through systematically analyzing the location data carried by user check-ins and comments, user location prediction can mine various user behavior patterns and their personal preferences, thus determining the visiting location of users in the future | ||
| Applicants should master basic knowledge on data mining | | Applicants should master basic knowledge on data mining | ||