# A deeper understanding of term vectors and the more like this query

**URL:** <https://discuss.elastic.co/t/a-deeper-understanding-of-term-vectors-and-the-more-like-this-query/40384>\
**Category:** Elasticsearch\
**Created:** [January 28, 2016, 3:58pm UTC](https://discuss.elastic.co/t/a-deeper-understanding-of-term-vectors-and-the-more-like-this-query/40384 "2016-01-28T15:58:17Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![bbaronas](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/bbaronas/32/116240_2.png) [@bbaronas](https://discuss.elastic.co/u/bbaronas)\
**Post date:** [January 28, 2016, 3:58pm UTC](https://discuss.elastic.co/t/a-deeper-understanding-of-term-vectors-and-the-more-like-this-query/40384/1 "2016-01-28T15:58:17Z")

</div>

I am trying to gain a deeper understanding of the more\_like\_this query. As I understand it, the more\_like\_this query will derive term vectors on either the string fields specified, or on all of the string fields of a specified document or documents, and then use those terms as a query to find other documents in the index. Further, I understand that these terms are derived using tf/idf based on values found not only in the particular field, but also across that same field in each document containing that field.

First, is this a correct understanding of how the more\_like\_this query works?

Next, if that is the case, does that mean more\_like\_this essentially ignores other terms that may exist in the field, but did not make it into the max\_query\_terms?

Finally, assuming the above questions are the case, what are some suggestions on maximizing "quality" terms besides just providing a list of stopwords to drop out of the running? Should I leverage max\_doc\_freq in a manner similar to the cutoff\_frequency in the common terms query?

I am very new to search and I am trying to gain some insight on how some of these query tools work.

Thank you.

---

<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:** [July 5, 2017, 11:20pm UTC](https://discuss.elastic.co/t/a-deeper-understanding-of-term-vectors-and-the-more-like-this-query/40384/2 "2017-07-05T23:20:46Z")

</div>