# Term suggester score calculation

**URL:** <https://discuss.elastic.co/t/term-suggester-score-calculation/171143>\
**Category:** Elasticsearch\
**Created:** [March 6, 2019, 3:27pm UTC](https://discuss.elastic.co/t/term-suggester-score-calculation/171143 "2019-03-06T15:27:04Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![anderstr](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/anderstr/32/41627_2.png) [@anderstr](https://discuss.elastic.co/u/anderstr)\
**Post date:** [March 6, 2019, 3:27pm UTC](https://discuss.elastic.co/t/term-suggester-score-calculation/171143/1 "2019-03-06T15:27:04Z")

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How is the score calculated in the term suggester?

[https://www.elastic.co/guide/en/elasticsearch/reference/current/search-suggesters-term.html](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-suggesters-term.html)

I assume it is a combination of term frequency and string distance. However I am seeing some surprising results:

Searching for "chreme" in my index with a term suggester (default settings) suggests "chrome" (score 0.833, frequency 48) and "creme" (score 0.8, frequency 2050). I believe both of these suggestions have an edit distance of 1, so how does the low frequency suggestion get a higher score?

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<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [April 3, 2019, 3:27pm UTC](https://discuss.elastic.co/t/term-suggester-score-calculation/171143/2 "2019-04-03T15:27:15Z")

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