这是我在弹性搜索上的字段:
"keywordName": {
"type": "text",
"analyzer": "custom_stop"
}
这是我的分析仪:
"custom_stop": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"my_stop",
"my_snow",
"asciifolding"
]
}
这是我的过滤器:
"my_stop": {
"type": "stop",
"stopwords": "_french_"
},
"my_snow" : {
"type" : "snowball",
"language" : "French"
}
以下是我的文档索引(在我的唯一字段中:keywordName):
“canne a peche”,“canne”,“canne a peche telescopique”,“iphone 8”,“iphone 8 case”,“iphone 8 cover”,“iphone 8 charger”,“iphone 8 new”
当我搜索“canne”时,它会给我“canne”文档,这就是我想要的:
GET ads/_search
{
"query": {
"match": {
"keywordName": {
"query": "canne",
"operator": "and"
}
}
},
"size": 1
}
当我搜索“canneàpêche”时,它给了我“canne a peche”,这也没关系。同样适用于“CannesàPêche” - > “canne a peche” - >行。
这是一个棘手的部分:当我搜索“iphone 8”时,它给了我“iphone 8 cover”而不是“iphone 8”。如果我改变大小,我设置5(因为它返回包含“iphone 8”的5个结果)。我看到“iphone 8”是得分方面的第4个结果。第一个是“iphone 8 cover”,然后是“iphone 8 case”,然后是“iphone 8 new”,最后是“iphone 8”......
以下是查询的结果:
{
"took": 5,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 5,
"max_score": 1.4009607,
"hits": [
{
"_index": "ads",
"_type": "keyword",
"_id": "iphone 8 cover",
"_score": 1.4009607,
"_source": {
"keywordName": "iphone 8 cover"
}
},
{
"_index": "ads",
"_type": "keyword",
"_id": "iphone 8 case",
"_score": 1.4009607,
"_source": {
"keywordName": "iphone 8 case"
}
},
{
"_index": "ads",
"_type": "keyword",
"_id": "iphone 8 new",
"_score": 0.70293105,
"_source": {
"keywordName": "iphone 8 new"
}
},
{
"_index": "ads",
"_type": "keyword",
"_id": "iphone 8",
"_score": 0.5804671,
"_source": {
"keywordName": "iphone 8"
}
},
{
"_index": "ads",
"_type": "keyword",
"_id": "iphone 8 charge",
"_score": 0.46705723,
"_source": {
"keywordName": "iphone 8 charge"
}
}
]
}
}
如何保持关键词“canne a peche”(口音,大写字母,复数词)的灵活性,还告诉他如果有完全匹配(“iphone 8”=“iphone 8”),请给出我确切的keywordName?
答案 0 :(得分:1)
匹配查询使用tf / idf算法。这意味着您将获得按频率排序的模糊搜索结果。如果你想在完全匹配的情况下获得结果,你应该在之前创建一个query_string case,如果没有结果则使用你的匹配查询。
答案 1 :(得分:1)
我建议这样的事情:
"keywordName": {
"type": "text",
"analyzer": "custom_stop",
"fields": {
"raw": {
"type": "keyword"
}
}
}
查询:
{
"query": {
"bool": {
"should": [
{
"match": {
"keywordName": {
"query": "iphone 8",
"operator": "and"
}
}
},
{
"term": {
"keywordName.raw": {
"value": "iphone 8"
}
}
}
]
}
},
"size": 10
}