# Improve scoring of search results for a multi-field, weighted Elasticsearch query

**URL:** <https://discuss.elastic.co/t/improve-scoring-of-search-results-for-a-multi-field-weighted-elasticsearch-query/208380>\
**Category:** Elasticsearch\
**Created:** [November 18, 2019, 7:39pm UTC](https://discuss.elastic.co/t/improve-scoring-of-search-results-for-a-multi-field-weighted-elasticsearch-query/208380 "2019-11-18T19:39:48Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![Chintan\_Tank](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/chintan_tank/32/57885_2.png) [@Chintan\_Tank](https://discuss.elastic.co/u/Chintan_Tank)\
**Post date:** [November 18, 2019, 7:39pm UTC](https://discuss.elastic.co/t/improve-scoring-of-search-results-for-a-multi-field-weighted-elasticsearch-query/208380/1 "2019-11-18T19:39:48Z")

</div>

I am using Elasticsearch in an app & I am trying to understand the scoring for search relevancy because I am getting some interesting results.

Some of the fields,

```
# (this is a search only field and is composed of first_name, middle_name, last_name. I have set full_name as the target for `copy_to`)
* full_name 
    type: text
    norms: false

    fields:
      autocomplete:
        type: text
        analyzer: autocomplete_l18n
        search_analyzer: autocomplete_search_l18n
      search:
        type: search_as_you_type

# Same as full_name it is made up of other fields & purely search field
* address 
  type: text          
  fields:
    autocomplete:
      type: text
      analyzer: autocomplete_l18n
      search_analyzer: autocomplete_search_l18n

```

The custom analyzers I created are,

```
# For any fields that requires autocomplete feature
autocomplete_l18n:
  type: custom
  tokenizer: standard
  filter:
  - en_stop_filter
  - lowercase
  - autocomplete_filter

# For any fields that would be searched using autocomplete feature
autocomplete_search_l18n:
  type: custom
  tokenizer: standard
  filter:
  - en_stop_filter
  - lowercase

```

There are other fields I use in search but they don't match for my query, so I am ommitting them here.

I have bunch of indexed entries of the form,

```
* Foo Baz | 1 Amityville
* Foobar Baz | 2 Townsville
* Foo Baz | 3 Lolsville
* Foodar Baz | 4 Townsville
* Foo Alice | 5 Lolsville
* Alex Baz | 6 Amityville
* Foo Bob | 7 Townsville

(Format here is: `full_name` | `address`)

```

The query I have used is,

```auto
{
  "query": {
    "bool": {
      "must": [
        {
          "bool": {
            "must": [
              [
                {
                  "bool": {
                    "should": [
                      {
                        "multi_match": {
                          "query": "Foo Baz Lolsville",
                          "fields": [
                            "full_name.autocomplete^10",
                            "address.search^8"
                          ],
                          "type": "best_fields",
                          "operator": "or",
                          "fuzziness": "AUTO"
                        }
                      },
                      {
                        "multi_match": {
                          "query": "Foo Baz Lolsville",
                          "fields": [
                            "full_name.autocomplete^10",
                            "address.search^8"
                          ],
                          "type": "cross_fields",
                          "operator": "or"
                        }
                      },
                      {
                        "multi_match": {
                          "query": "Foo Baz Lolsville",
                          "fields": [
                            "full_name.autocomplete^10",
                            "address.search^8"
                          ],
                          "type": "phrase_prefix",
                          "operator": "or"
                        }
                      }
                    ],
                    "minimum_should_match": 1
                  }
                }
              ]
            ]
          }
        }
      ]
    }
  }
}

```

Now when I search with,  
"Foo Baz 3 Lolsville" or "Foo Baz Lolsville"

I would expect to get "Foo Baz | 3 Lolsville" as the very first result. But that seems to be the 3rd or 4th result or even lower.

I turned on explain mode in the query & it seems that the search on `address` is performed BUT it is part of a "max of sub-scores". And hence instead of increasing the scroes it is basically a noop.

What can I do here to ensure that scoring from different fields are added, and not part of "max of"?

---

<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:** [December 16, 2019, 7:40pm UTC](https://discuss.elastic.co/t/improve-scoring-of-search-results-for-a-multi-field-weighted-elasticsearch-query/208380/2 "2019-12-16T19:40:00Z")

</div>

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