Elasticsearch:使用文档中的自定义分数字段影响评分 [英] Elasticsearch: Influence scoring with custom score field in document

问题描述

我有一组通过 NLP 算法从文本中提取的单词，以及每个文档中每个单词的相关分数.

I have a set of words extracted out of text through NLP algos, with associated score for each word in every document.

例如:

document 1: {  "vocab": [ {"wtag":"James Bond", "rscore": 2.14 }, 
                          {"wtag":"world", "rscore": 0.86 }, 
                          ...., 
                          {"wtag":"somemore", "rscore": 3.15 }
                        ] 
            }

document 2: {  "vocab": [ {"wtag":"hiii", "rscore": 1.34 }, 
                          {"wtag":"world", "rscore": 0.94 },
                          ...., 
                          {"wtag":"somemore", "rscore": 3.23 } 
                        ] 
            }

我希望每个文档中匹配的 wtag 的 rscore s 影响 ES 赋予它的 _score，可能相乘或添加到_score，影响结果文档的最终 _score(依次为顺序).有什么办法可以做到这一点吗?

I want rscores of matched wtag in each document to affect the _score given to it by ES, maybe multiplied or added to the _score, to influence the final _score (in turn, order) of the resulting documents. Is there any way to achieve this?

推荐答案

另一种方法是使用嵌套文档:

Another way of approaching this would be to use nested documents:

首先设置映射使 vocab 成为一个嵌套文档，这意味着每个 wtag/rscore 文档将作为一个单独的文档在内部被索引:

First setup the mapping to make vocab a nested document, meaning that each wtag/rscore document would be indexed internally as a separate document:

curl -XPUT "http://localhost:9200/myindex/" -d'
{
  "settings": {"number_of_shards": 1}, 
  "mappings": {
    "mytype": {
      "properties": {
        "vocab": {
          "type": "nested",
          "fields": {
            "wtag": {
              "type": "string"
            },
            "rscore": {
              "type": "float"
            }
          }
        }
      }
    }
  }
}'

然后将您的文档编入索引:

Then index your docs:

curl -XPUT "http://localhost:9200/myindex/mytype/1" -d'
{
  "vocab": [
    {
      "wtag": "James Bond",
      "rscore": 2.14
    },
    {
      "wtag": "world",
      "rscore": 0.86
    },
    {
      "wtag": "somemore",
      "rscore": 3.15
    }
  ]
}'

curl -XPUT "http://localhost:9200/myindex/mytype/2" -d'
{
  "vocab": [
    {
      "wtag": "hiii",
      "rscore": 1.34
    },
    {
      "wtag": "world",
      "rscore": 0.94
    },
    {
      "wtag": "somemore",
      "rscore": 3.23
    }
  ]
}'

然后运行一个 nested 查询来匹配所有的嵌套文档，并将每个匹配的嵌套文档的 rscore 值相加:

And run a nested query to match all the nested documents and add up the values of rscore for each nested document which matches:

curl -XGET "http://localhost:9200/myindex/mytype/_search" -d'
{
  "query": {
    "nested": {
      "path": "vocab",
      "score_mode": "sum",
      "query": {
        "function_score": {
          "query": {
            "match": {
              "vocab.wtag": "james bond world"
            }
          },
          "script_score": {
            "script": "doc["rscore"].value"
          }
        }
      }
    }
  }
}'

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