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|{{Hl2}} |'''Initial Readings'''
|{{Hl2}} |'''Initial Readings'''
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| '''A survey of point of interests recommendation ( )'''
| '''A survey of 5G (assigned to Hu)'''
| Point of interest recommendation with social and geographical influence. Abstract: Point of interest (POI) recommendation, a service which can help people discover useful and interesting locations has emerged rapidly with the development of location-based social networks (LBSNs), like Foursquare, Gowalla and Wechat.
| Reading papers about 5G, especially its influence on big data and give a survey
| Basic machine learning knowledge
|  
| [Shichang Ding--sding@gwdg.de]
| [Shichang Ding--sding@gwdg.de]
| [https://dl.acm.org/citation.cfm?id=3210042]
|
|-
| '''A survey of human mobility and deep learning (assigned to Sun)'''
| Reading papers about HM and DL and give a survey
|
| [Shichang Ding--sding@gwdg.de]
|
|-
|-
| '''Network Meets AI & Machine Learning (assigned to hamed roknizadeh)'''
| '''Network Meets AI & Machine Learning (assigned to hamed roknizadeh)'''
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|  
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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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|[http://www.net.informatik.uni-goettingen.de/?q=people/yachao-shao Yachao Shao]
|[http://www.net.informatik.uni-goettingen.de/?q=people/yachao-shao Yachao Shao]
|-
|-
|'''Cache Replacement in Mobile Edge Computing'''
|'''Cache Replacement in Mobile Edge Computing (assigned to Marjan Olesch)'''
| Implement the algorithm for cache replacement in mobile edge computing.
| Implement the algorithm for cache replacement in mobile edge computing.
| Basic networking knowledge, at least familiar with one programming language (eg. C or Python).   
| Basic networking knowledge, at least familiar with one programming language (eg. C or Python).   
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-yali-yuan Yali Yuan]
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-yali-yuan Yali Yuan]
|[https://ieeexplore.ieee.org/abstract/document/8513863]
|[https://ieeexplore.ieee.org/abstract/document/8513863]
|
|-
| '''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
| Applicants should master basic knowledge on data mining
| [Shuai Xu--shuai.xu@cs.uni-goettingen.de ]
| [http://staff.ustc.edu.cn/~cheneh/paper_pdf/2015/Yingzi-Wang-KDD.pdf][https://www.sciencedirect.com/science/article/pii/S1084804518300444][https://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/viewPaper/11900][https://ieeexplore.ieee.org/abstract/document/7498303]
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|-
|'''RoMS: An intelligent monitoring system for road surface distresses inspection using smart phones (still available for three students)'''
| Design and develop an intelligent road condition monitoring system.
| Basic machine learning knowledge, familiar with Python. 
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-yali-yuan Yali Yuan]
|[https://ieeexplore.ieee.org/abstract/document/7297863]
|}
|}


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