I am using a LSA/TF-IDF/BM25/Ensemble models for text search and finally calculating similarity score to rank my search. I would like to decide a threshold value for the score, below which I would not like to display anything. Eg: If my similarity score is less than 0.7, I would like to return "No Result Found".

I know there wont be any specific value that I can use here, but I would appreciate suggestions on how I can find that value?

My Thoughts: Idea 1: I can calculate the similarity scores for all past searches and try to find average of top 10 scores for each search, and take a final mean of all those value (Not sure if it would be a good idea).

Idea 2: Deploy model to production with top 15-20 search results and wait to collect users click results, so one insight after collecting result for a month could be, 95% of the time user does not go to any results having score less than 0.60 or something.

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    $\begingroup$ There's no perfect answer, your ideas seem good to me. I would say that the 2nd one is certainly better (it's practically a kind of evaluation) but it's more complex to apply. In case it helps, see related question. $\endgroup$
    – Erwan
    Sep 25, 2022 at 21:25
  • $\begingroup$ @Erwan Thank You for your response, and indeed the related question you shared is helpful. $\endgroup$ Sep 26, 2022 at 6:43


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