# Synonyms result scoring

**URL:** <https://discuss.elastic.co/t/synonyms-result-scoring/152523>\
**Category:** Elasticsearch\
**Created:** [October 15, 2018, 3:18pm UTC](https://discuss.elastic.co/t/synonyms-result-scoring/152523 "2018-10-15T15:18:51Z")\
**Posts on this page:** 1\
**Showing post:** 2

<div class="post-metadata">

**Author:** ![abdon](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/abdon/32/9195_2.png) [@abdon](https://discuss.elastic.co/u/abdon)\
**Post date:** [October 15, 2018, 4:34pm UTC](https://discuss.elastic.co/t/synonyms-result-scoring/152523/2 "2018-10-15T16:34:32Z")

</div>

Great questions!

1. Synonyms score the same as an exact match. There is no automatic preference for exact matches.
2. The length of a field is an important factor that determines the score: shorter fields score higher than longer fields. What you're seeing is that the documents with a shorter field (6 terms) score higher than the document with a longer field (18 terms).

If you want to understand how a score is calculated, you can add `"explain": true` to a search request, and Elasticsearch will tell you exactly how the score for each hit was calculated:

```auto
GET wheat_syn/wheat/_search
{
  "explain": true, 
  "query": {
    "match": {
      "description": "wheat"
    }
  }
}

```

Some suggestions: if you are looking at scores for a small dataset like this, consider creating the index with one shard (instead of the default 5). Otherwise the scoring may be unexpected as explained [here](https://www.elastic.co/guide/en/elasticsearch/guide/current/relevance-is-broken.html).

Also, consider indexing the data twice: once with synonyms and once without synonyms. You can do that by using [multi-fields](https://www.elastic.co/guide/en/elasticsearch/reference/current/multi-fields.html). Your index creation command would become:

```auto
PUT wheat_syn
{
  "mappings": {
    "wheat": {
      "properties": {
        "description": {
          "type": "text",
          "fields": {
            "synonyms": {
              "type": "text",
              "analyzer": "syn_text"
            },
            "keyword": {
              "type": "keyword",
              "ignore_above": 256
            }
          }
        }
      }
    }
  },
  "settings": {
    "number_of_shards": 1,
    "analysis": {
      "filter": {
        "autophrase_syn": {
          "type": "synonym",
          "synonyms": [
            "triticum aestivum => triticum_aestivum",
            "bread wheat => bread_wheat"
          ]
        },
        "wheat_syn": {
          "type": "synonym",
          "tokenizer": "keyword",
          "synonyms": [
            "triticum_aestivum, bread_wheat, wheat"
          ]
        }
      },
      "analyzer": {
        "syn_text": {
          "tokenizer": "standard",
          "filter": [
            "lowercase",
            "autophrase_syn",
            "wheat_syn"
          ]
        }
      }
    }
  }
}

```

Now, you can use a `bool` query to search simultaneously with and without synonyms:

```auto
GET wheat_syn/wheat/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "description.synonyms": "wheat"
          }
        }
      ],
      "should": [
        {
          "match": {
            "description": {
              "query": "wheat"
            }
          }
        }
      ]
    }
  }
}

```

Those documents that contain the exact term are the only ones that match the `should` clause (which does not use synonyms). As a result, those docs will get a higher score and rank at the top of the results.

Synonyms can be tricky to set up correctly. We will soon launch an [on-demand training course about synonyms](https://www.elastic.co/training/specializations/elasticsearch-advanced-search/improving-search-with-synonyms) that covers topics like this.

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_[View the full topic](https://discuss.elastic.co/t/synonyms-result-scoring/152523)._