elasticsearch 理解elasticsearch查询分数解释
我试图破解elasticsearch响应中的explain API。但是有点迷路了。这对我来说有点难理解。是否有任何简单的指针或链接可以更具体地解释JSON?我对TF、IDF和VSM中的余弦相似性有一个了解。但更具体地说,需要一些关于JSON的指针。如果我能找到一个简单的数学表达式来解释这个JSON,那将是一个理想的选择
elasticsearch 理解elasticsearch查询分数解释,
elasticsearch,lucene,tf-idf,cosine-similarity,
elasticsearch,Lucene,Tf Idf,Cosine Similarity,我试图破解elasticsearch响应中的explain API。但是有点迷路了。这对我来说有点难理解。是否有任何简单的指针或链接可以更具体地解释JSON?我对TF、IDF和VSM中的余弦相似性有一个了解。但更具体地说,需要一些关于JSON的指针。如果我能找到一个简单的数学表达式来解释这个JSON,那将是一个理想的选择 { "_explanation": { "value": 7.937373, "description": "sum of:", "details"
{
"_explanation": {
"value": 7.937373,
"description": "sum of:",
"details": [
{
"value": 2.4789724,
"description": "weight(FirstName:M80806 in 35) [PerFieldSimilarity], result of:",
"details": [
{
"value": 2.4789724,
"description": "score(doc=35,freq=1.0), product of:",
"details": [
{
"value": 0.37350902,
"description": "queryWeight, product of:",
"details": [
{
"value": 6.6369815,
"description": "idf(docFreq=720, maxDocs=202323)"
},
{
"value": 0.056276944,
"description": "queryNorm"
}
]
},
{
"value": 6.6369815,
"description": "fieldWeight in 35, product of:",
"details": [
{
"value": 1,
"description": "tf(freq=1.0), with freq of:",
"details": [
{
"value": 1,
"description": "termFreq=1.0"
}
]
},
{
"value": 6.6369815,
"description": "idf(docFreq=720, maxDocs=202323)"
},
{
"value": 1,
"description": "fieldNorm(doc=35)"
}
]
}
]
}
]
},
{
"value": 2.6825092,
"description": "weight(FirstName:M8086 in 35) [PerFieldSimilarity], result of:",
"details": [
{
"value": 2.6825092,
"description": "score(doc=35,freq=1.0), product of:",
"details": [
{
"value": 0.38854012,
"description": "queryWeight, product of:",
"details": [
{
"value": 6.9040728,
"description": "idf(docFreq=551, maxDocs=202323)"
},
{
"value": 0.056276944,
"description": "queryNorm"
}
]
},
{
"value": 6.9040728,
"description": "fieldWeight in 35, product of:",
"details": [
{
"value": 1,
"description": "tf(freq=1.0), with freq of:",
"details": [
{
"value": 1,
"description": "termFreq=1.0"
}
]
},
{
"value": 6.9040728,
"description": "idf(docFreq=551, maxDocs=202323)"
},
{
"value": 1,
"description": "fieldNorm(doc=35)"
}
]
}
]
}
]
},
{
"value": 2.7758915,
"description": "weight(FirstName:MHMT in 35) [PerFieldSimilarity], result of:",
"details": [
{
"value": 2.7758915,
"description": "score(doc=35,freq=1.0), product of:",
"details": [
{
"value": 0.3952451,
"description": "queryWeight, product of:",
"details": [
{
"value": 7.0232153,
"description": "idf(docFreq=489, maxDocs=202323)"
},
{
"value": 0.056276944,
"description": "queryNorm"
}
]
},
{
"value": 7.0232153,
"description": "fieldWeight in 35, product of:",
"details": [
{
"value": 1,
"description": "tf(freq=1.0), with freq of:",
"details": [
{
"value": 1,
"description": "termFreq=1.0"
}
]
},
{
"value": 7.0232153,
"description": "idf(docFreq=489, maxDocs=202323)"
},
{
"value": 1,
"description": "fieldNorm(doc=35)"
}
]
}
]
}
]
}
]
}
}
使用RubyGem,您将获得更具可读性的“解释”,例如
require 'elasticsearch'
client = Elasticsearch::Client.new
result = client.explain index: "megacorp", type: "employee", id: "1", q: "last_name:Smith"
puts Elasticsearch::API::Response::ExplainResponse.new(result["explanation"]).render
#=>
1.0 = 1.0(fieldWeight)
1.0 = 1.0(tf(1.0)) x 1.0(idf(2/3)) x 1.0(fieldNorm)
1.0 = 1.0(termFreq=1.0)
这将有助于你了解分数,如果没有请让我知道解释的事情。。。。这也应该有所帮助