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Seminar on Internet Technologies (Summer 2019): Difference between revisions
Seminar on Internet Technologies (Summer 2019) (view source)
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| '''Smart health for citizens and the role of big data''' | | '''Smart health for citizens and the role of big data (Assigned to Tapashi Gosswami)''' | ||
| Nowadays, the development of wearable devices enables people to monitor personal health related indexes like heart rate, blood pressure and sleeping time, as well as personal daily activities. The devices could record data throughout a whole day and generate large amount of data. By studying the above data of certain patients, it is possible to find out how the change of the health relevant indexes and personal activities could infect the physical condition and cause disease. | | Nowadays, the development of wearable devices enables people to monitor personal health related indexes like heart rate, blood pressure and sleeping time, as well as personal daily activities. The devices could record data throughout a whole day and generate large amount of data. By studying the above data of certain patients, it is possible to find out how the change of the health relevant indexes and personal activities could infect the physical condition and cause disease. | ||
| The student should perform a review of the medical big data for advanced diagnosis | | The student should perform a review of the medical big data for advanced diagnosis | ||
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| '''User Location Prediction based on Geo-social Networking Data''' | | '''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 | ||