如何在弹性搜索中用可扩展的前缀和后缀匹配短语？ [英] How to match a phrase in elastic-search with expandable prefix and suffix?

问题描述

我们有一个用例，我们希望在弹性搜索中匹配词组，但是除了词组查询之外，我们还想搜索部分词组。

We have a use case in which we want to match phrases in elastic-search, but in addition to phrase query we also want to search partial phrases.

示例：

搜索短语： welcome you或 lcome you或 welcome yo或 lcome yo，这应与包含短语的文档匹配：

Search phrase: "welcome you" or "lcome you" or "welcome yo" or "lcome yo" this should match to documents containing phrases:

欢迎您

我们欢迎您

欢迎您使用

我们欢迎您使用

ie我们希望通过执行短语查询来维护单词的顺序，该短语查询具有添加的功能，该功能返回给我们结果，其中包含作为部分子字符串的短语，并且其前缀和后缀可扩展到某些可配置的长度。
在弹性中，我发现了类似的内容' match_phrase_prefix '，但是

i.e. we want to maintain the ordering of words by doing a phrase query with added functionality that is returns us results which contains phrase as a partial substring and with prefix and suffix expandable to certain configurable length. In elastic I found something similar 'match_phrase_prefix' but it only match phrases which starts with a particular prefix.

Ex返回结果以d前缀开头：

Ex return results starting with d prefix:

$ curl -XGET localhost:9200/startswith/test/_search?pretty -d '{
    "query": {
        "match_phrase_prefix": {
            "title": {
                "query": "d",
                "max_expansions": 5
            }
        }
    }
}'

还有什么方法可以实现后缀吗？

Is there any way that I could achieve this for suffix as well ?

推荐答案

我强烈建议您研究 shingle 令牌过滤器。

I would strongly encourage you to look into the shingle token filter.

您可以定义一个索引机智定制分析器，它利用带状疱状图以将令牌本身之外的一组后续令牌索引在一起。

You can define an index with a custom analyzer that leverages shingles in order to index a set of subsequent tokens together in addition to the tokens themselves.

curl -XPUT localhost:9200/startswith -d '{
  "settings": {
      "analysis": {
        "analyzer": {
          "my_shingles": {
            "tokenizer": "standard",
            "filter": [
              "lowercase",
              "shingles"
            ]
          }
        },
        "filter": {
          "shingles": {
            "type": "shingle",
            "min_shingle_size": 2,
            "max_shingle_size": 2,
            "output_unigrams": true
          }
        }
      }
  },
  "mappings": {
    "test": {
      "properties": {
        "title": {
          "type": "text",
          "analyzer": "my_shingles"
        }
      }
    }
  }
}'

例如，我们欢迎您被索引为以下令牌

For instance, we welcome you to would be indexed as the following tokens

• 我们


• 我们欢迎


• 欢迎


• 欢迎您


• 您


• 您要


• 至

• we
• we welcome
• welcome
• welcome you
• you
• you to
• to

然后您可以索引一些示例文档：

Then you can index a few sample documents:

curl -XPUT localhost:9200/startswith/test/_bulk -d '
{"index": {}}
{"title": "welcome you"}
{"index": {}}
{"title": "we welcome you"}
{"index": {}}
{"title": "welcome you to"}
{"index": {}}
{"title": "we welcome you to"}
'

最后，您可以运行以下查询来匹配上面的所有四个文档，像这样：

Finally, you can run the following query to match all four documents above, like this:

curl -XPOST localhost:9200/startswith/test/_search -d '{
   "query": {
       "match": {"title": "welcome you"}
   }
}'

请注意，此方法比功能强大match_phrase_prefix 查询，因为它允许您在文本正文中的任何位置（无论是开头还是结尾）匹配后续标记。

Note that this approach is more powerful than the match_phrase_prefix query, because it allows you to match subsequent tokens anywhere in your body of text, whether at the beginning or the end.

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