Seminar on Internet Technologies (Winter 2018/2019): Difference between revisions

Line 90: Line 90:
|-
|-
|-
|-
| ''' Mobile spatial and temporal data based user profiles identification'''
| ''' Mobile spatial and temporal data based user profiles identification(Assigned to Knopp, Cornelius)'''
| When people using their APPs in smartphones, the communication base station will catch the URL requests from each customer. Each record is assigned to a specific user ID, and includes a time stamp and an URL request. Moreover, most frequently used APPs need location service provided by assembled GPS sensor in the smartphone, and some coordinates are contained in the URLs. With the information above, each user could be modeled by a set of spatial-temporal data. Different users could show different patterns, which includes the features like POI preference, trajectory type, usage frequency at different time and etc. We aim to cluster the users in different categories according to their spatial-temporal data.
| When people using their APPs in smartphones, the communication base station will catch the URL requests from each customer. Each record is assigned to a specific user ID, and includes a time stamp and an URL request. Moreover, most frequently used APPs need location service provided by assembled GPS sensor in the smartphone, and some coordinates are contained in the URLs. With the information above, each user could be modeled by a set of spatial-temporal data. Different users could show different patterns, which includes the features like POI preference, trajectory type, usage frequency at different time and etc. We aim to cluster the users in different categories according to their spatial-temporal data.