Thesis Topic Details
Topic ID: |
2989 | |
Title: |
Matching Algorithms for Recommendation in Online Dating | |
Supervisor: |
Wayne Wobcke | |
Research Area: |
Artificial Intelligence | |
| Associated Staff | ||
|---|---|---|
Assessor: |
Mike Bain | |
| Topic Details | ||
Status: |
Active | |
Type: |
R & D | |
Programs: |
CS SE | |
Group Suitable: |
No | |
Industrial: |
No | |
Pre-requisites: |
Interest in Machine Learning | |
Description: |
The objective is to compare a number of algorithms on data from a real-world online dating site to work out the best methods to use in recommending suitable matches at various times in the user's interaction with the site. | |
Comments: |
-- | |
| Past Student Reports | ||
| No Reports Available. Contact the supervisor for more information.
Check out all available reports in the CSE Thesis Report Library. NOTE: only current CSE students can login to view and select reports to download. |
||