# Multiple Nested Object Function Scoring

**URL:** <https://discuss.elastic.co/t/multiple-nested-object-function-scoring/305626>\
**Category:** Elasticsearch\
**Tags:** eql-elastic-query-language\
**Created:** [May 25, 2022, 3:32pm UTC](https://discuss.elastic.co/t/multiple-nested-object-function-scoring/305626 "2022-05-25T15:32:32Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![vp\_tech](https://avatars.discourse-cdn.com/v4/letter/v/47e85d/32.png) [@vp\_tech](https://discuss.elastic.co/u/vp_tech)\
**Post date:** [May 25, 2022, 3:32pm UTC](https://discuss.elastic.co/t/multiple-nested-object-function-scoring/305626/1 "2022-05-25T15:32:32Z")

</div>

##### ES Version: 6.8

I have an index storing documents that contain a list of nested `tag` objects. Each `tag` object has a text field (for the tag itself) and a float field representing a `weight` that describes the strength of association between the tag and the outer document and is thus useful for scoring.

I need to create a query that returns documents with matching tags and scores them based on _the weights of all matching tags_.

##### What I have so far:

Index:

```auto
{
  "nested-scoring-test" : {
    "mappings" : {
      "record" : {
        "properties" : {
          "tags" : {
            "type" : "nested",
            "properties" : {
              "tag" : {
                "type" : "text"
              },
              "weight" : {
                "type" : "float"
              }
            }
          },
          "name" : {
            "type" : "text"
          }
        }
      }
    }
  }
}

```

##### Test Document

```auto
{
  "name": "Test",
  "tags": [
    {
      "tag": "Captain Falcon Only",
      "weight": 0.5
    },
    {
      "tag": "Captain Kirk Only",
      "weight": 0.25
    },
    {
      "tag": "Falcon Punch Only",
      "weight": 0.1
    }
  ]
}

```

##### Query So Far:

```auto
{
  "query": {
    "nested": {
      "path": "tag",
      "query": {
        "function_score": {
          "query": {
            "constant_score": {
              "filter": {
                "match": {
                  "tag.tag": "Only"
                }
              }
            }
          },
          "functions": [
            {
              "field_value_factor": {
                "field": "tag.weight",
                "factor": 1
              }
            }
          ],
          "boost_mode": "replace"
        }
      }
    }
  }
}

```

For this query, I would expect the returned score to be **0.85**. However, it's actually **0.28333333**. In fact, the returned score is actually lower (0.375) than if I would try to match the word "Captain" which only has two matching tags instead of three. This makes me think TF\_IDF is getting involved even though I'm trying to set my scores absolutely anyway.

The explain is also not super helpful:

```auto
"explanation" : {
    "value" : 0.28333333,
    "description" : "sum of:",
    "details" : [ {
      "value" : 0.28333333,
      "description" : "Score based on 3 child docs in range from 0 to 2, best match:",
      "details" : [ {
        "value" : 0.5,
        "description" : "sum of:",
        "details" : [ {
          "value" : 0.5,
          "description" : "min of:",
          "details" : [ {
            "value" : 0.5,
            "description" : "field value function: none(doc['tag.weight'].value * factor=1.0)",
            "details" : []
          }, {
            "value" : 3.4028235E38,
            "description" : "maxBoost",
            "details" : []
          } ]
        }, {
          "value" : 0.0,
          "description" : "match on required clause, product of:",
          "details" : [ {
            "value" : 0.0,
            "description" : "# clause",
            "details" : []
          }, {
            "value" : 1.0,
            "description" : "_type:__tags",
            "details" : []
          } ]
        } ]
      } ]
  }
}

```

You can see the step of "Score based on 3 child docs..." is seemingly magic and probably where TF-IDF gets involved.

However, I would be fine with these results but the TF-IDF seems to be localized to the outer document. Case in point, if I add another document that looks like this:

```auto
{
  "name": "Test Again",
  "tags": [
    {
      "tag": "Officer Eddie Only",
      "weight": 0.5
    },
    {
      "tag": "Officer Ward Excluded",
      "weight": 0.25
    },
    {
      "tag": "Officer Earhart Excluded",
      "weight": 0.1
    }
  ]
}

```

The original query will return it as the top result with a score of **0.5**.

How can I modify my query so that my scoring works as I expect?

---

<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:** [June 22, 2022, 3:32pm UTC](https://discuss.elastic.co/t/multiple-nested-object-function-scoring/305626/2 "2022-06-22T15:32:51Z")

</div>

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