20_深度探秘搜索技术_混合使用match和近似匹配实现召回率与精准度的平衡

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/article/_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
          }
        }
      }
    }
  }
}

第一步: 我们先利用must搜索 ,相关度高的排在下面了

GET /forum/article/_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"
]
}
}
]
}
}

第二步: 在should中加入match_phrase,然后就可以得到正确结果

GET /forum/article/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"content": "java spark"
}
}
],
"should": [
{
"match_phrase": {
"content": {
"query": "java spark",
"slop": 50
}
}
}
]
}
}
}

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