Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
Next revision Both sides next revision
teaching:projh402 [2021/08/18 14:11]
ezimanyi [Symbolic trajectories]
teaching:projh402 [2021/08/18 15:03]
ezimanyi [Course objective]
Line 3: Line 3:
  
 ===== Course objective ===== ===== Course objective =====
-The course PROJ-H-402 is managed by Dr. Mauro Birattari. Please refer to the course description page http://​iridia.ulb.ac.be/​proj-h-402/​index.php/​Main_Page ​for the rules concerning the project. ​ What follows is a list of project proposals supervised by academic members of the WIT laboratory.+The course PROJ-H-402 is managed by Dr. Mauro Birattari. Please refer to the [[http://​iridia.ulb.ac.be/​wiki/PROJ-H-402_-_Computing_Project:​_Rules|course description page]] ​  for the rules concerning the project. ​ What follows is a list of project proposals supervised by academic members of the WIT laboratory.
  
 ===== Projects in Mobility Databases ===== ===== Projects in Mobility Databases =====
Line 65: Line 65:
 ===== Symbolic trajectories ===== ===== Symbolic trajectories =====
  
-Symbolic trajectories enable to attach semantic information to geometric trajectories . Essentially,​ symbolic trajectories are just time-dependent labels representing,​ for example, the names of roads traversed obtained by map matching, transportation modes, speed profile, cells of a cellular network, behaviors of animals, cinemas within 2km distance, and so forth. Symbolic trajectories can be combined with geometric trajectories to obtain annotated trajectories.+Symbolic trajectories enable to attach semantic information to geometric trajectories. Essentially,​ symbolic trajectories are just time-dependent labels representing,​ for example, the names of roads traversed obtained by map matching, transportation modes, speed profile, cells of a cellular network, behaviors of animals, cinemas within 2km distance, and so forth. Symbolic trajectories can be combined with geometric trajectories to obtain annotated trajectories.
  
 The goal of this project is to explore how to implement symbolic trajectories in MobilityDB. This implementation will be based on the ttext (temporal text) data type implemented in MobilityDB and will explore how to extend it with regular expressions. This extension can be inspired from the [[https://​www.postgresql.org/​docs/​13/​functions-json.html|jsonb]] data type implemented in PostgreSQL. ​ The goal of this project is to explore how to implement symbolic trajectories in MobilityDB. This implementation will be based on the ttext (temporal text) data type implemented in MobilityDB and will explore how to extend it with regular expressions. This extension can be inspired from the [[https://​www.postgresql.org/​docs/​13/​functions-json.html|jsonb]] data type implemented in PostgreSQL. ​
 
teaching/projh402.txt · Last modified: 2022/09/06 10:39 by ezimanyi