我有一个充满关键字的索引,并根据这些关键字我想从输入文本中提取关键字。
以下是示例关键字索引。请注意,关键字也可以是多个单词,或者基本上它们是唯一的标记。
{
"hits": {
"total": 2000,
"hits": [
{
"id": 1,
"keyword": "thousand eyes"
},
{
"id": 2,
"keyword": "facebook"
},
{
"id": 3,
"keyword": "superdoc"
},
{
"id": 4,
"keyword": "quora"
},
{
"id": 5,
"keyword": "your story"
},
{
"id": 6,
"keyword": "Surgery"
},
{
"id": 7,
"keyword": "lending club"
},
{
"id": 8,
"keyword": "ad roll"
},
{
"id": 9,
"keyword": "the honest company"
},
{
"id": 10,
"keyword": "Draft kings"
}
]
}
}
现在,如果我输入文字“我在facebook上看到了借阅俱乐部的消息,你的故事和quora”,搜索的输出应该是 [“借阅俱乐部”, “facebook”,“你的故事”,“quora”] 。搜索也应该是 case insensetive
答案 0 :(得分:7)
只有一种方法可以做到这一点。您必须将数据编入索引作为关键字并使用带状疱疹进行搜索:
见这个复制品:
首先,我们将创建两个自定义分析器:关键字和带状疱疹:
PUT test
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer_keyword": {
"type": "custom",
"tokenizer": "keyword",
"filter": [
"asciifolding",
"lowercase"
]
},
"my_analyzer_shingle": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"asciifolding",
"lowercase",
"shingle"
]
}
}
}
},
"mappings": {
"your_type": {
"properties": {
"keyword": {
"type": "string",
"index_analyzer": "my_analyzer_keyword",
"search_analyzer": "my_analyzer_shingle"
}
}
}
}
}
现在让我们使用您提供的内容创建一些示例数据:
POST /test/your_type/1
{
"id": 1,
"keyword": "thousand eyes"
}
POST /test/your_type/2
{
"id": 2,
"keyword": "facebook"
}
POST /test/your_type/3
{
"id": 3,
"keyword": "superdoc"
}
POST /test/your_type/4
{
"id": 4,
"keyword": "quora"
}
POST /test/your_type/5
{
"id": 5,
"keyword": "your story"
}
POST /test/your_type/6
{
"id": 6,
"keyword": "Surgery"
}
POST /test/your_type/7
{
"id": 7,
"keyword": "lending club"
}
POST /test/your_type/8
{
"id": 8,
"keyword": "ad roll"
}
POST /test/your_type/9
{
"id": 9,
"keyword": "the honest company"
}
POST /test/your_type/10
{
"id": 10,
"keyword": "Draft kings"
}
最后查询运行搜索:
POST /test/your_type/_search
{
"query": {
"match": {
"keyword": "I saw the news of lending club on facebook, your story and quora"
}
}
}
这就是结果:
{
"took": 6,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 4,
"max_score": 0.009332742,
"hits": [
{
"_index": "test",
"_type": "your_type",
"_id": "2",
"_score": 0.009332742,
"_source": {
"id": 2,
"keyword": "facebook"
}
},
{
"_index": "test",
"_type": "your_type",
"_id": "7",
"_score": 0.009332742,
"_source": {
"id": 7,
"keyword": "lending club"
}
},
{
"_index": "test",
"_type": "your_type",
"_id": "4",
"_score": 0.009207102,
"_source": {
"id": 4,
"keyword": "quora"
}
},
{
"_index": "test",
"_type": "your_type",
"_id": "5",
"_score": 0.0014755741,
"_source": {
"id": 5,
"keyword": "your story"
}
}
]
}
}
那么它在幕后做了什么?
é
变为e
)和小写过滤器(不区分大小写的搜索)。因此,例如Draft kings
被编入索引为draft kings