如何在天蓝色搜索中将精确匹配排名更高

Question

我在 Azure 搜索中有一个索引，其中包含名字和姓氏等个人数据。

当我使用

之类的查询搜索 3 个字母的姓氏时

rau&searchFields=LastName

/indexes/customers-index/docs?api-version=2016-09-01&search=rau&searchFields=LastName

找到了名字 rau，但它在最后很远。

{
"@odata.context": "myurl/indexes('customers-index')/$metadata#docs(ID,FirstName,LastName)",
"value": [
    {
        "@search.score": 8.729204,
        "ID": "someid",
        "FirstName": "xxx",
        "LastName": "Liebetrau"
    },
    {
        "@search.score": 8.729204,
        "ID": "someid",
        "FirstName": "xxx",
        "LastName": "Damerau"
    },
    {
        "@search.score": 8.729204,
        "ID": "someid",
        "FirstName": "xxx",
        "LastName": "Rau"

更靠前的是像 "Liebetrau"、"Damerau".

这样的名字

有没有办法在顶部进行完全匹配？

编辑

使用 RestApi 查询索引定义

GET https://myproduct.search.windows.net/indexes('customers-index')?api-version=2015-02-28-Preview

返回姓氏

 "name": "LastName",
  "type": "Edm.String",
  "searchable": true,
  "filterable": true,
  "retrievable": true,
  "sortable": true,
  "facetable": true,
  "key": false,
  "indexAnalyzer": "prefix",
  "searchAnalyzer": "standard",
  "analyzer": null,
  "synonymMaps": []

编辑 1

分析器定义

      "scoringProfiles": [],
  "defaultScoringProfile": null,
  "corsOptions": null,
  "suggesters": [],
  "analyzers": [
    {
      "name": "prefix",
      "tokenizer": "standard",
      "tokenFilters": [
        "lowercase",
        "my_edgeNGram"
      ],
      "charFilters": []
    }
  ],
  "tokenizers": [],
  "tokenFilters": [
    {
      "name": "my_edgeNGram",
      "minGram": 2,
      "maxGram": 20,
      "side": "back"
    }
  ],
  "charFilters": []

编辑 2

最后指定我在查询时使用的 ScoringProfile

   {
    "name": "person-index",  
    "fields": [

       {
      "name": "ID",
      "type": "Edm.String",
      "searchable": false,
      "filterable": true,
      "retrievable": true,
      "sortable": true,
      "facetable": true,
      "key": true,
      "indexAnalyzer": null,
      "searchAnalyzer": null,
      "analyzer": null

    }
    ,
    {
      "name": "LastName",
      "type": "Edm.String",
      "searchable": true,
      "filterable": true,
      "retrievable": true,
      "sortable": true,
      "facetable": true,
      "key": false,
      "analyzer":  "my_standard"

    },
     {
      "name": "PartialLastName",
      "type": "Edm.String",
      "searchable": true,
      "filterable": true,
      "retrievable": true,
      "sortable": true,
      "facetable": true,
      "key": false,
      "indexAnalyzer": "prefix",
      "searchAnalyzer": "standard",
      "analyzer": null

    }
    ],
    "analyzers":[
    {
      "name":"my_standard",
      "@odata.type":"#Microsoft.Azure.Search.CustomAnalyzer",
      "tokenizer":"standard_v2",
      "tokenFilters":[ "lowercase", "asciifolding" ]
    },
    {
      "name":"prefix",
      "@odata.type":"#Microsoft.Azure.Search.CustomAnalyzer",
      "tokenizer":"standard_v2",
      "tokenFilters":[ "lowercase", "my_edgeNGram" ]
    }
  ],
  "tokenFilters":[
    {
      "name":"my_edgeNGram",
      "@odata.type":"#Microsoft.Azure.Search.EdgeNGramTokenFilterV2",
      "minGram":2,
      "maxGram":20,
      "side": "back"
    }
  ],
  "scoringProfiles":[
  {
    "name":"exactFirst",
    "text":{
      "weights":{ "LastName":2, "PartialLastName":1 }     
    }
  }
]
}

Answer 1

在 LastName 字段上设置的分析器 "prefix" 为姓名 Liebetrau 生成以下术语：au, rau, trau, etrau, betrau, ebetrau, iebetrau, libetrau。这些 edge ngrams 的长度范围从单词的后面开始，从 2 到 20，如索引定义中的 my_edgeNGram 标记过滤器中所定义。分析器将以相同的方式处理其他名称。当您搜索姓名 rau 时，它会匹配所有以这些字符结尾的姓名。这就是为什么结果集中的所有文档都具有相同的相关性得分。

您可以使用 Analyze API.

测试您的分析器配置

要了解有关自定义分析器的更多信息，请转至 here and here。

希望对您有所帮助

如何在天蓝色搜索中将精确匹配排名更高

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