Optimal usage of conversations received in a chatbot
2 comments
We used to use svc for classification in the early days of chatbots, but switched to tensorflow
We are using a bidirectional lstm model for sequence classification.
We are using a bidirectional lstm model for sequence classification.
Retrain your model with the new data, or use it to build a better model.
Also we have a feedback dashboard where the admin can tag and validate incoming user queries with correct class names (similar to what existing platforms provide). This is fine until a certain level but becomes impossible later.
So now we have a few (5k) tagged queries and a lot (350k) untagged user queries. Is there any way we can use these to enhance our system ?