Hi Everyone,

I have a documents search engine, and the users have ability to Rate the search result for any query they make. For the first versions of Search engine, I am using Universal Sentence Encoder to generate document embeddings, and at the time of search User search queries are also embedded and the documents with most closest embeddings are presented in search result.

User can rate a documents from the search result, on some scale, say 0 to 5 (0 being Not Relevant and 5 is Very relevant)

Using this kind of feedback is there a way we can fine tune the search results?

One idea is using BERT with triplet loss, where we can use:

Anchor : User Search Query

Contradiction : Document which User found Not Relevant

Entailment: Document user found very relevant

Anybody experience in doing this? or any other ideas, suggestions , papers are welcome.

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