召回率
比如你搜索一个java spark
,总共有100个doc
,能返回多少个doc
作为结果,就是召回率,recall
精准度
比如你搜索一个java spark
,能不能尽可能让包含java spark
,或者是java
和spark
离的很近的doc
,排在最前面,precision
直接用match_phrase
短语搜索,会导致必须所有term
都在doc field
中出现,而且距离在slop
限定范围内,才能匹配上match phrase
,proximity match
,要求doc必须包含所有的term
,才能作为结果返回;如果某一个doc
可能就是有某个term
没有包含,那么就无法作为结果返回java spark --> hello world java -->
就不能返回了
java spark --> hello world, java spark -->
才可以返回
近似匹配的时候,召回率比较低,精准度太高了
但是有时可能我们希望的是匹配到几个term
中的部分,就可以作为结果出来,这样可以提高召回率。同时我们也希望用上match_phrase
根据距离提升分数的功能,让几个term
距离越近分数就越高,优先返回
就是优先满足召回率,意思,java spark
,包含java
的也返回,包含spark
的也返回,包含java
和spark
的也返回;同时兼顾精准度,就是包含java
和spark
,同时java
和spark
离的越近的doc
排在最前面
此时可以用bool
组合match query
和match_phrase query
一起,来实现上述效果
GET /forum/_search
{
"query": {
"bool": {
"must": {
"match": {
"title": {
"query": "java spark" --> java或spark或java spark,java和spark靠前,但是没法区分java和spark的距离,也许java和spark靠的很近,但是没法排在最前面
}
}
},
"should": {
"match_phrase": { --> 在slop以内,如果java spark能匹配上一个doc,那么就会对doc贡献自己的relevance score,如果java和spark靠的越近,那么就分数越高
"title": {
"query": "java spark",
"slop": 50
}
}
}
}
}
}
GET /forum/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"content": "java spark"
}
}
]
}
}
}
{
"took": 5,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0.68640786,
"hits": [
{
"_index": "forum",
"_type": "article",
"_id": "2",
"_score": 0.68640786,
"_source": {
"articleID": "KDKE-B-9947-#kL5",
"userID": 1,
"hidden": false,
"postDate": "2017-01-02",
"tag": [
"java"
],
"tag_cnt": 1,
"view_cnt": 50,
"title": "this is java blog",
"content": "i think java is the best programming language",
"sub_title": "learned a lot of course",
"author_first_name": "Smith",
"author_last_name": "Williams",
"new_author_last_name": "Williams",
"new_author_first_name": "Smith",
"followers": [
"Tom",
"Jack"
]
}
},
{
"_index": "forum",
"_type": "article",
"_id": "5",
"_score": 0.68324494,
"_source": {
"articleID": "DHJK-B-1395-#Ky5",
"userID": 3,
"hidden": false,
"postDate": "2017-03-01",
"tag": [
"elasticsearch"
],
"tag_cnt": 1,
"view_cnt": 10,
"title": "this is spark blog",
"content": "spark is best big data solution based on scala ,an programming language similar to java spark",
"sub_title": "haha, hello world",
"author_first_name": "Tonny",
"author_last_name": "Peter Smith",
"new_author_last_name": "Peter Smith",
"new_author_first_name": "Tonny",
"followers": [
"Jack",
"Robbin Li"
]
}
}
]
}
}
使用 match 和 近似匹配实现召回率与精准度的平衡:
GET /forum/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"content": "java spark"
}
}
],
"should": [
{
"match_phrase": {
"content": {
"query": "java spark",
"slop": 50
}
}
}
]
}
}
}
{
"took": 5,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 1.258609,
"hits": [
{
"_index": "forum",
"_type": "article",
"_id": "5",
"_score": 1.258609,
"_source": {
"articleID": "DHJK-B-1395-#Ky5",
"userID": 3,
"hidden": false,
"postDate": "2017-03-01",
"tag": [
"elasticsearch"
],
"tag_cnt": 1,
"view_cnt": 10,
"title": "this is spark blog",
"content": "spark is best big data solution based on scala ,an programming language similar to java spark",
"sub_title": "haha, hello world",
"author_first_name": "Tonny",
"author_last_name": "Peter Smith",
"new_author_last_name": "Peter Smith",
"new_author_first_name": "Tonny",
"followers": [
"Jack",
"Robbin Li"
]
}
},
{
"_index": "forum",
"_type": "article",
"_id": "2",
"_score": 0.68640786,
"_source": {
"articleID": "KDKE-B-9947-#kL5",
"userID": 1,
"hidden": false,
"postDate": "2017-01-02",
"tag": [
"java"
],
"tag_cnt": 1,
"view_cnt": 50,
"title": "this is java blog",
"content": "i think java is the best programming language",
"sub_title": "learned a lot of course",
"author_first_name": "Smith",
"author_last_name": "Williams",
"new_author_last_name": "Williams",
"new_author_first_name": "Smith",
"followers": [
"Tom",
"Jack"
]
}
}
]
}
}