改善建议的相关性

Question

在某些情况下，我需要根据给定的文本查找建议。 我的基本需求是获取建议，以便首先需要完全匹配的对象才是模糊的。我正在使用下面描述的脚本索引我的name字段作为建议的输入。我已附上我选择的解决方案。

例如搜索 amazon仅返回以amazon开头的文本，而不返回“ theamazon”或“ welcome to amazon”。 我该怎么做才能得到这样的结果？另外，诸如theamazon或cometoamazon之类的文本呢？我正在使用两个不同的完成建议器来获得准确和模糊的结果。任何帮助深表感谢。我所有的代码如下。请随时询问有关代码的任何不清楚之处。

                 PUT search_queries_sug/
             {
                "settings": {
                "analysis": {
                    "filter": {
                        "autocomplete_filter": { 
                            "type":     "edge_ngram",
                            "min_gram": 2,
                            "max_gram": 30
                        }

                    },

                "analyzer": {
                    "autocomplete": {
                        "type":      "custom",
                        "tokenizer": "keyword",

                        "filter": [
                            "lowercase",
                            "autocomplete_filter" 

                        ]
                    }

                }
            }
        }
    }

映射看起来像-

PUT search_queries_sug/_mapping/realtime
{
  "realtime": {
        "properties": {
          "suggest_exact" : {
          "type" : "completion",
          "analyzer":"autocomplete",
          "preserve_position_increments":false,
          "preserve_separators" : false,
          "search_analyzer":"standard"

              },
              "suggest_fuzzy" : {
          "type" : "completion",
          "analyzer":"autocomplete",
          "preserve_position_increments":false,
          "preserve_separators" : false,
          "search_analyzer":"standard"

              },
          "datetime": {
            "type": "date"
          },
          "name": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword",
                "ignore_above": 256
              }
            }
          },
          "search_count": {
            "type": "long"
          }
        }
      }
}

这就是我对建议编制索引的方式-

POST /search_queries_sug/realtime/_update_by_query?
{
  "query": { 
    "match_all":{}
  },
  "script": "ctx._source.suggest_exact = ctx._source.name;ctx._source.suggest_fuzzy = ctx._source.name "
}

这是查询之前的文档外观-

{
        "_index": "search_queries_sug",
        "_type": "realtime",
        "_id": "40d3b294ed2ef49f12185d698b2f9e3d",
        "_score": 1,
        "_source": {
          "datetime": "2018-07-19T15:09:55Z",
          "name": "Sing along with Goutam",
          "suggest_fuzzy": "Sing along with Goutam",
          "search_count": 1,
          "suggest_exact": "Sing along with Goutam"
        }
      }

查询后，结果为-

"hits": {
    "total": 0,
    "max_score": 0,
    "hits": []
  },
  "suggest": {
    "text-suggest-exact": [
      {
        "text": "amazon",
        "offset": 0,
        "length": 6,
        "options": [
          {
            "text": "Amazon",
            "_index": "search_queries_sug",
            "_type": "realtime",
            "_id": "b3b3a6ac74ecbd56bcdbefa4799fb9df",
            "_score": 6,
            "_source": {
              "datetime": "2018-07-24T20:58:40Z",
              "name": "Amazon",
              "suggest_fuzzy": "Amazon",
              "search_count": 1,
              "suggest_exact": "Amazon"
            }

    ],
    "text-suggest-fuzzy": [
      {
        "text": "amazon",
        "offset": 0,
        "length": 6,
        "options": [
          {
            "text": "Amazon",
            "_index": "search_queries_sug",
            "_type": "realtime",
            "_id": "b3b3a6ac74ecbd56bcdbefa4799fb9df",
            "_score": 5,
            "_source": {
              "datetime": "2018-07-24T20:58:40Z",
              "name": "Amazon",
              "suggest_fuzzy": "Amazon",
              "search_count": 1,
              "suggest_exact": "Amazon"
            }
          },
          {
            "text": "Amazing dance",
            "_index": "search_queries_sug",
            "_type": "realtime",
            "_id": "6a32e5fb887e6ab362ab00c74ea62e07",
            "_score": 4,
            "_source": {
              "datetime": "2018-07-27T09:48:41Z",
              "name": "Amazing dance",
              "suggest_fuzzy": "Amazing dance",
              "search_count": 1,
              "suggest_exact": "Amazing dance"
            }
          }