# Normalizing Scores

**URL:** https://discuss.elastic.co/t/normalizing-scores/17749
**Category:** Elasticsearch
**Created:** [May 27, 2014, 11:34am UTC](https://discuss.elastic.co/t/normalizing-scores/17749 "2014-05-27T11:34:21Z")
**Posts on this page:** 1
**Showing post:** 5

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### Author: ![harto](https://avatars.discourse-cdn.com/v4/letter/h/bb73d2/32.png) [@harto](https://discuss.elastic.co/u/harto)
#### Post date: [August 2, 2016, 2:55am UTC](https://discuss.elastic.co/t/normalizing-scores/17749/5 "2016-08-02T02:55:33Z")

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Hello, sorry for bumping this very old topic.

I'm also interested in knowing if it's possible to normalize `_score` values into the range `0,1.0` (where the top result has score `1.0`).

The proposed solution floors scores above `1.0`, but if I understood correctly the OP wanted to know if all scores could effectively be divided by `max_score`.

The reason this is interesting to me is: I don't know how to determine weights for functions in a `function_score` query. I.e. if a given query can produce `_score` values in an arbitrary range, how can I know if a weight of 1, 5, 100 or 50000 is effective?

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_[View the full topic](https://discuss.elastic.co/t/normalizing-scores/17749)._