# Fuzzy queries relevance score detailed explanation **URL:** \ **Category:** Elasticsearch\ **Created:** [January 19, 2016, 9:06pm UTC](https://discuss.elastic.co/t/fuzzy-queries-relevance-score-detailed-explanation/39597 "2016-01-19T21:06:29Z")\ **Posts on this page:** 1\ **Showing post:** 2
**Author:** ![Mark\_Harwood](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/mark_harwood/32/10538_2.png) [@Mark\_Harwood](https://discuss.elastic.co/u/Mark_Harwood)\ **Post date:** [January 20, 2016, 10:56am UTC](https://discuss.elastic.co/t/fuzzy-queries-relevance-score-detailed-explanation/39597/2 "2016-01-20T10:56:52Z")
Fuzzy queries take a single user-provided term and produce several Lucene TermQuery variants, each of which are boosted with a score that reflects the edit distance (the boost for a non-fuzzy query term is usually 1.0 i.e. no boosting effect.). This used to be mixed in with the usual Lucene IDF ranking but to ill effect [1]. Modern versions of fuzzy query now "lie" about document frequencies of the auto-expanded term variants to prevent IDF issues like this one linked. [1] [When searching for 'Boss' with fuzziness, get higher score for 'Bose' than 'Boss'. ? How Comes !?!?](https://discuss.elastic.co/t/when-searching-for-boss-with-fuzziness-get-higher-score-for-bose-than-boss-how-comes/21662/8) --- _[View the full topic](https://discuss.elastic.co/t/fuzzy-queries-relevance-score-detailed-explanation/39597)._