We have built a data-driven platform that allows users to:
- Express and track their mental status
- Anonymously connect and empathize with other users based on likelihood of improvement through a chat channel.
- Flutter working demo app with the basic features of our platform.
- Matchmaking model based on a large pretrained embedding transformer mapping documents to latent space representations gathering similarities and user profile extracted features. The model is re-trained through a metric lerning approach based on a custom adaptation of a contrastive loss which considers user feedback and status tracking data.
- Chat assistant bot modeled as an agent in a chat enironment where conversation score-based rewards and penalizations are extracted to apply reinforcement learning.
- Sample Dataset containing a definition and some rows of a lightweight pseudo-datawharehouse.
- Re-training our matching model based on user feedback and improvement results
- Conversation data defining an environment for a virtual chat assistant dealing with ice-breakers, destructive conversations,etc. aiming to maximize connection quality.
The more usage the app has the better performance the AI could bring.
Jordi Baroja
Marçal Comajoan
Mauro Filomeno
Marc Franquesa
Pol Puigdemont