Elasticsearch 模糊查询 - 最大编辑不能按预期工作

Question

我最近在我们的搜索查询字符串中添加了 "fuzzy operator" 和模糊查询设置，以防止用户输入错误（例如 "zamestnanost" 与 "zamestnani")

POST /my_index/_search
{
   "query": {
      "query_string": {
         "query": "+(content:zamestnanost~)",
         "fuzzy_prefix_length": 3,
         "fuzzy_min_sim": 0.5, 
         "fuzzy_max_expansions": 50
      }
   }
}

据我了解模糊查询设置，fuzzy_min_sim = 0.5 应该允许对原始查询进行 length(query)*0.5 编辑（在本例中为 6 编辑）。

然而，它甚至不匹配 "closer" 个单词（标记），例如

"zamestnani"
"zamestnany"

我有这种 st运行ge 的感觉，它仍然只匹配索引中最大的单词。原始查询字符串的 2 次编辑（这是模糊查询中的默认编辑计数）。

我也运行对我的查询进行了解释，我认为结果支持这个假设。 _explanation 看起来像这样：

"_explanation": {
   "value": 0.057083897,
   "description": "sum of:",
   "details": [
      {
         "value": 0.023866946,
         "description": "weight(content:zamestnano^0.8 in 0) [PerFieldSimilarity], result of:",
         "details": [
            {
               "value": 0.023866946,
               "description": "score(doc=0,freq=4.0), product of:",
               "details": [
                  {
                     "value": 0.66062796,
                     "description": "queryWeight, product of:",
                     "details": [
                        {
                           "value": 0.8,
                           "description": "boost"
                        },
                        {
                           "value": 4.624341,
                           "description": "idf(docFreq=1, maxDocs=75)"
                        },
                        {
                           "value": 0.17857353,
                           "description": "queryNorm"
                        }
                     ]
                  },
                  {
                     "value": 0.036127664,
                     "description": "fieldWeight in 0, product of:",
                     "details": [
                        {
                           "value": 2,
                           "description": "tf(freq=4.0), with freq of:",
                           "details": [
                              {
                                 "value": 4,
                                 "description": "termFreq=4.0"
                              }
                           ]
                        },
                        {
                           "value": 4.624341,
                           "description": "idf(docFreq=1, maxDocs=75)"
                        },
                        {
                           "value": 0.00390625,
                           "description": "fieldNorm(doc=0)"
                        }
                     ]
                  }
               ]
            }
         ]
      },
      {
         "value": 0.03321695,
         "description": "weight(content:zamestnanos^0.9090909 in 0) [PerFieldSimilarity], result of:",
         "details": [
            {
               "value": 0.03321695,
               "description": "score(doc=0,freq=6.0), product of:",
               "details": [
                  {
                     "value": 0.7507135,
                     "description": "queryWeight, product of:",
                     "details": [
                        {
                           "value": 0.9090909,
                           "description": "boost"
                        },
                        {
                           "value": 4.624341,
                           "description": "idf(docFreq=1, maxDocs=75)"
                        },
                        {
                           "value": 0.17857353,
                           "description": "queryNorm"
                        }
                     ]
                  },
                  {
                     "value": 0.044247173,
                     "description": "fieldWeight in 0, product of:",
                     "details": [
                        {
                           "value": 2.4494898,
                           "description": "tf(freq=6.0), with freq of:",
                           "details": [
                              {
                                 "value": 6,
                                 "description": "termFreq=6.0"
                              }
                           ]
                        },
                        {
                           "value": 4.624341,
                           "description": "idf(docFreq=1, maxDocs=75)"
                        },
                        {
                           "value": 0.00390625,
                           "description": "fieldNorm(doc=0)"
                        }
                     ]
                  }
               ]
            }
         ]
      }
   ]
}

只有查询 "zamestnano" 和 "zemestnanos" 是使用模糊查询编辑创建的。

我对模糊查询的设置理解对吗？你能指出我的错误吗？

非常感谢每一个想法！

Answer 1

来自the documentation：

0.0..1.0

[1.7.0] Deprecated in 1.7.0. Support for similarity will be removed in Elasticsearch 2.0. converted into an edit distance using the formula: length(term) * (1.0 - fuzziness), eg a fuzziness of 0.6 with a term of length 10 would result in an edit distance of 4. Note: in all APIs except for the Fuzzy Like This Query, the maximum allowed edit distance is 2.

最简单的复查方法是使用 validate API:

GET _validate/query?explain&index=my_index
{
  "query": {
    "query_string": {
      "query": "+(content:zamestnanost~)",
      "fuzzy_prefix_length": 3,
      "fuzzy_min_sim": 0.5,
      "fuzzy_max_expansions": 50
    }
  }
}

结果如下：

   "explanations": [
      {
         "index": "test",
         "valid": true,
         "explanation": "+content:zamestnanost~2"
      }
   ]

显示 ES 将在查询中使用的实际编辑距离：zamestnanost~2。

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