我有一个Elasticsearch索引，我有一些数据。我实现了did-you-mean功能，因此当用户写错拼写的内容时，它可以收到带有正确单词的建议。
我使用短语建议，因为我需要短语的建议，例如名称，问题是索引中不存在一些建议。
示例：
document in the index: coding like a master
search: Codning like a boss
suggestion: <em>coding</em> like a boss
search result: not found
我的问题是，我的索引中没有符合指定建议的短语，因此它会向我推荐不存在的短语，因此会给我一个未找到的搜索。
我该怎么办？不应该短语建议者为索引中实际存在的短语提供建议吗？
在这里，我会留下相应的查询，映射和设置以防万一你需要它。
设置和映射
{
"settings": {
"index": {
"number_of_shards": 3,
"number_of_replicas": 1,
"search.slowlog.threshold.fetch.warn": "2s",
"index.analysis.analyzer.default.filter.0": "standard",
"index.analysis.analyzer.default.tokenizer": "standard",
"index.analysis.analyzer.default.filter.1": "lowercase",
"index.analysis.analyzer.default.filter.2": "asciifolding",
"index.priority": 3,
"analysis": {
"analyzer": {
"suggests_analyzer": {
"tokenizer": "lowercase",
"filter": [
"lowercase",
"asciifolding",
"shingle_filter"
],
"type": "custom"
}
},
"filter": {
"shingle_filter": {
"min_shingle_size": 2,
"max_shingle_size": 3,
"type": "shingle"
}
}
}
}
},
"mappings": {
"my_type": {
"properties": {
"suggest_field": {
"analyzer": "suggests_analyzer",
"type": "string"
}
}
}
}
}
查询
{
"DidYouMean": {
"text": "Codning like a boss",
"phrase": {
"field": "suggest_field",
"size": 1,
"gram_size": 1,
"confidence": 2.0
}
}
}
感谢您的帮助。
答案 0 :(得分：10)
这实际上是预期的。如果您使用analyze api分析文档，您将更好地了解正在发生的事情。
GET suggest_index/_analyze?text=coding like a master&analyzer=suggests_analyzer
这是输出
{
"tokens": [
{
"token": "coding",
"start_offset": 0,
"end_offset": 6,
"type": "word",
"position": 1
},
{
"token": "coding like",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 1
},
{
"token": "coding like a",
"start_offset": 0,
"end_offset": 13,
"type": "shingle",
"position": 1
},
{
"token": "like",
"start_offset": 7,
"end_offset": 11,
"type": "word",
"position": 2
},
{
"token": "like a",
"start_offset": 7,
"end_offset": 13,
"type": "shingle",
"position": 2
},
{
"token": "like a master",
"start_offset": 7,
"end_offset": 20,
"type": "shingle",
"position": 2
},
{
"token": "a",
"start_offset": 12,
"end_offset": 13,
"type": "word",
"position": 3
},
{
"token": "a master",
"start_offset": 12,
"end_offset": 20,
"type": "shingle",
"position": 3
},
{
"token": "master",
"start_offset": 14,
"end_offset": 20,
"type": "word",
"position": 4
}
]
}
正如您所看到的，有一个令牌＆＃34;编码＆＃34;为文本生成，因此它在您的索引中。 不建议您不在索引中。如果您严格要求词组搜索，那么您可能需要考虑使用keyword tokenizer。例如，如果您将映射更改为
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"suggests_analyzer": {
"tokenizer": "lowercase",
"filter": [
"lowercase",
"asciifolding",
"shingle_filter"
],
"type": "custom"
},
"raw_analyzer": {
"tokenizer": "keyword",
"filter": [
"lowercase",
"asciifolding"
]
}
},
"filter": {
"shingle_filter": {
"min_shingle_size": 2,
"max_shingle_size": 3,
"type": "shingle"
}
}
}
}
},
"mappings": {
"my_type": {
"properties": {
"suggest_field": {
"analyzer": "suggests_analyzer",
"type": "string",
"fields": {
"raw": {
"analyzer": "raw_analyzer",
"type": "string"
}
}
}
}
}
}
}
然后此查询将为您提供预期结果
{
"DidYouMean": {
"text": "codning lke a master",
"phrase": {
"field": "suggest_field.raw",
"size": 1,
"gram_size": 1
}
}
}
它不会显示＆＃34;像老板一样编码＆＃34; 。
编辑1
2）从您的评论以及在我自己的数据集上运行一些短语建议，我觉得更好的方法是使用collate选项phrase suggester提供，以便我们可以检查每个建议a query并且仅在它将从索引中取回任何文档时才给出建议。我还在映射中添加了stemmers以仅考虑根词。我正在使用light_english因为它不那么激进。 More就此而言。
映射的分析器部分现在看起来像这样
"analysis": {
"analyzer": {
"suggests_analyzer": {
"tokenizer": "standard",
"filter": [
"lowercase",
"english_possessive_stemmer",
"light_english_stemmer",
"asciifolding",
"shingle_filter"
],
"type": "custom"
}
},
"filter": {
"light_english_stemmer": {
"type": "stemmer",
"language": "light_english"
},
"english_possessive_stemmer": {
"type": "stemmer",
"language": "possessive_english"
},
"shingle_filter": {
"min_shingle_size": 2,
"max_shingle_size": 4,
"type": "shingle"
}
}
}
现在，此查询将为您提供所需的结果。
{
"suggest" : {
"text" : "appel on the tabel",
"simple_phrase" : {
"phrase" : {
"field" : "suggest_field",
"size" : 5,
"collate": {
"query": {
"inline" : {
"match_phrase": {
"{{field_name}}" : "{{suggestion}}"
}
}
},
"params": {"field_name" : "suggest_field"},
"prune": false
}
}
}
},
"size": 0
}
这会让你回到桌面上的 apple
这里使用了match_phrase查询，它将针对索引运行每个建议的短语。您可以制作"prune" : true并查看已建议的所有结果，无论匹配项如何。您可能需要考虑使用stop过滤器来避免使用停用词。
希望这会有所帮助!!