“你的意思是” 是搜索引擎中一个非常重要的功能，因为它们通过显示建议的术语来帮助用户，以便他可以进行更准确的搜索。比如，在百度中，我们进行搜索时，它通常会显示一些更为常用推荐的搜索选项来供我们选择：

 

为了创建 “你的意思是”，我们将使用 phrase suggester，因为通过它我们将能够建议句子更正，而不仅仅是术语。在我之前的文章 “Elasticsearch：如何实现短语建议 - phrase suggester”，我有涉及到这个问题。

首先，我们将使用一个 shingle 过滤器，因为它将提供一个分词，短语建议器将使用该标记来进行匹配并返回更正。有关 shingle 过滤器的描述，请阅读之前的文章 “Elasticsearch: Ngrams, edge ngrams, and shingles”。

准备数据

我们首先来定义映射：

PUT movies
{"settings": {"analysis": {"analyzer": {"en_analyzer": {"tokenizer": "standard","filter": ["lowercase","stop"]},"shingle_analyzer": {"type": "custom","tokenizer": "standard","filter": ["lowercase","shingle_filter"]}},"filter": {"shingle_filter": {"type": "shingle","min_shingle_size": 2,"max_shingle_size": 3}}}},"mappings": {"properties": {"title": {"type": "text","analyzer": "en_analyzer","fields": {"suggest": {"type": "text","analyzer": "shingle_analyzer"}}},"actors": {"type": "text","analyzer": "en_analyzer","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"description": {"type": "text","analyzer": "en_analyzer","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"director": {"type": "text","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"genre": {"type": "text","fields": {"keyword": {"type": "keyword","ignore_above": 256}}},"metascore": {"type": "long"},"rating": {"type": "float"},"revenue": {"type": "float"},"runtime": {"type": "long"},"votes": {"type": "long"},"year": {"type": "long"},"title_suggest": {"type": "completion","analyzer": "simple","preserve_separators": true,"preserve_position_increments": true,"max_input_length": 50}}}
}

我们接下来使用 _bulk 命令来写入一些文档到这个索引中去。我们使用这个链接中的内容。我们使用如下的方法：

POST movies/_bulk
{"index": {}}
{"title": "Guardians of the Galaxy", "genre": "Action,Adventure,Sci-Fi", "director": "James Gunn", "actors": "Chris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana", "description": "A group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.", "year": 2014, "runtime": 121, "rating": 8.1, "votes": 757074, "revenue": 333.13, "metascore": 76}
{"index": {}}
{"title": "Prometheus", "genre": "Adventure,Mystery,Sci-Fi", "director": "Ridley Scott", "actors": "Noomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron", "description": "Following clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.", "year": 2012, "runtime": 124, "rating": 7, "votes": 485820, "revenue": 126.46, "metascore": 65}....

 在上面，为了说明的方便，我省去了其它的文档。你需要把整个 movies.txt 的文件拷贝过来，并全部写入到 Elasticsearch 中。它共有1000 个文档。

搜索数据

现在让我们运行一个基本查询来查看 suggest 的结果：

GET movies/_search?filter_path=suggest
{"suggest": {"text": "transformers revenge of the falen","did_you_mean": {"phrase": {"field": "title.suggest","size": 5}}}
}

上面命令显示的结果为：

{"suggest": {"did_you_mean": [{"text": "transformers revenge of the falen","offset": 0,"length": 33,"options": [{"text": "transformers revenge of the fallen","score": 0.004467494},{"text": "transformers revenge of the fall","score": 0.00020402104},{"text": "transformers revenge of the face","score": 0.00006419608}]}]}
}

请注意，在几行中你已经获得了一些有希望的结果。

现在让我们通过使用更多短语建议功能来增加我们的查询。让我们使用 max_errors = 2，这样我们希望句子中最多有两个术语。 添加了 highlight 显示以突出​​显示建议的术语。

GET movies/_search?filter_path=suggest
{"suggest": {"text": "transformer revenge of the falen","did_you_mean": {"phrase": {"field": "title.suggest","size": 5,"confidence": 1,"max_errors":2,"highlight": {"pre_tag": "<strong>","post_tag": "</strong>"}}}}
}

上面命令返回的结果为：

{"suggest": {"did_you_mean": [{"text": "transformer revenge of the falen","offset": 0,"length": 32,"options": [{"text": "transformers revenge of the fallen","highlighted": "<strong>transformers</strong> revenge of the <strong>fallen</strong>","score": 0.004382903},{"text": "transformers revenge of the fall","highlighted": "<strong>transformers</strong> revenge of the <strong>fall</strong>","score": 0.00020015794},{"text": "transformers revenge of the face","highlighted": "<strong>transformers</strong> revenge of the <strong>face</strong>","score": 0.00006298054},{"text": "transformers revenge of the falen","highlighted": "<strong>transformers</strong> revenge of the falen","score": 0.00006159308},{"text": "transformer revenge of the fallen","highlighted": "transformer revenge of the <strong>fallen</strong>","score": 0.000048000533}]}]}
}

我们再改进一点好吗？ 我们添加了 “collate”，我们可以对每个结果执行查询，改进建议的结果。 我使用了带有 “and” 运算符的匹配项，以便在同一个句子中匹配所有术语。 如果我仍然想要不符合查询条件的结果，我使用 prune = true。

GET movies/_search?filter_path=suggest
{"suggest": {"text": "transformer revenge of the falen","did_you_mean": {"phrase": {"field": "title.suggest","size": 5,"confidence": 1,"max_errors":2,"collate": {"query": { "source" : {"match": {"{{field_name}}": {"query": "{{suggestion}}","operator": "and"}}}},"params": {"field_name" : "title"}, "prune" :true},"highlight": {"pre_tag": "<strong>","post_tag": "</strong>"}}}}
}

现在的结果是：

请注意，答案已更改，我有一个新字段 “collat​​e_match”，它指示结果中是否匹配整理规则（这是因为 prune = true）。

让我们设置 prune 为 false：

GET movies/_search?filter_path=suggest
{"suggest": {"text": "transformer revenge of the falen","did_you_mean": {"phrase": {"field": "title.suggest","size": 5,"confidence": 1,"max_errors":2,"collate": {"query": { "source" : {"match": {"{{field_name}}": {"query": "{{suggestion}}","operator": "and"}}}},"params": {"field_name" : "title"}, "prune" :false},"highlight": {"pre_tag": "<strong>","post_tag": "</strong>"}}}}
}

这次我们得到的结果是：

我们可以看到只有一个结果是最相关的建议。