Elasticsearch：文档pt.2中具有自定义得分字段的影响力得分
拥有这些文件：
{ "created_at" : "2017-07-31T20:30:14-04:00",
"description" : null,
"height" : 3213,
"id" : "1",
"tags" : [
{
"confidence" : 65.48948436785749,
"tag" : "beach"
},
{
"confidence" : 57.31950504425406,
"tag" : "sea"
},
{
"confidence" : 43.58207236617374,
"tag" : "coast"
},
{
"confidence" : 35.6857910950816,
"tag" : "sand"
},
{
"confidence" : 33.660057321079655,
"tag" : "landscape"
},
{
"confidence" : 32.53252312423727,
"tag" : "sky"
}
],
"width" : 5712,
"color" : "#0C0A07",
"boost_multiplier" : 1
}
和
{ "created_at" : "2017-07-31T20:43:17-04:00",
"description" : null,
"height" : 4934,
"id" : "2",
"tags" : [
{
"confidence" : 84.09123410403951,
"tag" : "mountain"
},
{
"confidence" : 56.412795342449456,
"tag" : "valley"
},
{
"confidence" : 48.36547551196872,
"tag" : "landscape"
},
{
"confidence" : 40.51100450186575,
"tag" : "mountains"
},
{
"confidence" : 33.14263528292239,
"tag" : "sky"
},
{
"confidence" : 31.064394646169404,
"tag" : "peak"
},
{
"confidence" : 29.372,
"tag" : "natural elevation"
}
],
"width" : 4016,
"color" : "#FEEBF9",
"boost_multiplier" : 1
}
我想获得基于每个标签的置信度值计算的_score。例如，如果您搜索“ mountain”，则显然应该仅返回ID为1的文档；如果您搜索“
landscape”，则得分2应该高于1，因为景观对2的置信度高于1（48.36 vs 33.66）。如果您搜索“ coast
landscape”，则此时间得分1应该高于2，因为doc 1在标签数组中同时包含了Coast和Landscape。我还想将分数与“
boost_multiplier”相乘，以增强某些文档的性能。
我在Elasticsearch中发现了这个问题：文档中具有自定义得分字段的影响力得分
但是，当我尝试接受的解决方案（我在我的ES服务器中启用脚本）时，无论搜索词如何，它都返回带有_score 1.0的两个文档。这是我尝试过的查询：
{ "query": {
"nested": {
"path": "tags",
"score_mode": "sum",
"query": {
"function_score": {
"query": {
"match": {
"tags.tag": "coast landscape"
}
},
"script_score": {
"script": "doc[\"confidence\"].value"
}
}
}
}
}
}
我还尝试了@yahermann在注释中建议的内容，将“ script_score”替换为“ field_value_factor”：{“ field”：“
confidence”}，结果仍然相同。知道为什么它会失败，或者有更好的方法吗？
只是为了全面了解，这是我使用的映射定义：
{ "mappings": {
"photo": {
"properties": {
"created_at": {
"type": "date"
},
"description": {
"type": "text"
},
"height": {
"type": "short"
},
"id": {
"type": "keyword"
},
"tags": {
"type": "nested",
"properties": {
"tag": { "type": "string" },
"confidence": { "type": "float"}
}
},
"width": {
"type": "short"
},
"color": {
"type": "string"
},
"boost_multiplier": {
"type": "float"
}
}
}
},
"settings": {
"number_of_shards": 1
}
}
在下面@Joanna的答案之后，我尝试了查询，但是实际上，无论我在匹配查询，coast，foo，bar中放置什么，它总是返回两个文档都带有_score1.0的文档，我在elasticsearch2.4上进行了尝试Docker中的.6、5.3、5.5.1。这是我得到的答复：
HTTP/1.1 200 OKContent-Type: application/json; charset=UTF-8
Content-Length: 1635
{"took":24,"timed_out":false,"_shards":{"total":5,"successful":5,"failed":0},"hits":{"total":2,"max_score":1.0,"hits":[{"_index":"my_index","_type":"my_type","_id":"2","_score":1.0,"_source":{
"created_at" : "2017-07-31T20:43:17-04:00",
"description" : null,
"height" : 4934,
"id" : "2",
"tags" : [
{
"confidence" : 84.09123410403951,
"tag" : "mountain"
},
{
"confidence" : 56.412795342449456,
"tag" : "valley"
},
{
"confidence" : 48.36547551196872,
"tag" : "landscape"
},
{
"confidence" : 40.51100450186575,
"tag" : "mountains"
},
{
"confidence" : 33.14263528292239,
"tag" : "sky"
},
{
"confidence" : 31.064394646169404,
"tag" : "peak"
},
{
"confidence" : 29.372,
"tag" : "natural elevation"
}
],
"width" : 4016,
"color" : "#FEEBF9",
"boost_multiplier" : 1
}
},{"_index":"my_index","_type":"my_type","_id":"1","_score":1.0,"_source":{
"created_at" : "2017-07-31T20:30:14-04:00",
"description" : null,
"height" : 3213,
"id" : "1",
"tags" : [
{
"confidence" : 65.48948436785749,
"tag" : "beach"
},
{
"confidence" : 57.31950504425406,
"tag" : "sea"
},
{
"confidence" : 43.58207236617374,
"tag" : "coast"
},
{
"confidence" : 35.6857910950816,
"tag" : "sand"
},
{
"confidence" : 33.660057321079655,
"tag" : "landscape"
},
{
"confidence" : 32.53252312423727,
"tag" : "sky"
}
],
"width" : 5712,
"color" : "#0C0A07",
"boost_multiplier" : 1
}
}]}}
我在SO上发现了这一点：Elasticsearch：带有“boost_mode”的“function_score”：“replace”忽略了函数得分
它的基本含义是，如果函数不匹配，则返回1。这是有道理的，但我正在对同一文档运行查询。令人困惑。
最终我发现了问题，我很愚蠢。ES101，如果您发送GET请求以搜索api，它将返回所有得分为1.0的文档：）您应该发送POST请求…非常感谢@Joanna，它运行良好！
回答：
您可以尝试使用此查询-它结合了得分：confidence和boost_multiplier字段：
{ "query": {
"function_score": {
"query": {
"bool": {
"should": [{
"nested": {
"path": "tags",
"score_mode": "sum",
"query": {
"function_score": {
"query": {
"match": {
"tags.tag": "landscape"
}
},
"field_value_factor": {
"field": "tags.confidence",
"factor": 1,
"missing": 0
}
}
}
}
}]
}
},
"field_value_factor": {
"field": "boost_multiplier",
"factor": 1,
"missing": 0
}
}
}
}
id=1仅具有此术语的文档具有该术语，得分为"_score": 100.27469。
id=2得分为“ _score”的文档：85.83046id=1得分为“ _score”的文档：59.7339
由于id=2具有较高confidence字段值的文档，其得分更高。
id=1得分为“ _score”的文档：160.00859id=2得分为“ _score”的文档：85.83046
尽管id=2具有的文档具有较高的confidence字段值，但是具有的文档id=1具有匹配的单词，因此得分更高。通过更改"factor":
1参数的值，您可以决定confidence应多少影响结果。
boost_muliplier字段
当我为一个新文档建立索引时，会发生更有趣的事情：假设它与具有的文档几乎相同，id=2但是我设置了"boost_multiplier" :
4和"id": 3：
{ "created_at" : "2017-07-31T20:43:17-04:00",
"description" : null,
"height" : 4934,
"id" : "3",
"tags" : [
...
{
"confidence" : 48.36547551196872,
"tag" : "landscape"
},
...
],
"width" : 4016,
"color" : "#FEEBF9",
"boost_multiplier" : 4
}
使用coast landscapeterm 运行相同的查询将返回三个文档：
id=3得分为“ _score”的文档：360.02664id=1得分为“ _score”的文档：182.09859id=2得分为“ _score”的文档：90.00666
尽管的文档id=3只有一个匹配的单词（landscape），但其boost_multiplier值大大提高了评分。在此处，"factor":
1您还可以使用决定该值应增加多少分值，并"missing": 0确定如果没有索引该字段应发生什么。
以上是 Elasticsearch：文档pt.2中具有自定义得分字段的影响力得分 的全部内容， 来源链接： utcz.com/qa/407431.html
