Getting the document with searched term first, before its synonyms [Elastic] - elasticsearch

Question

I think I should explain my problem with an example:
Assume that I've created index with synonym analyzer and I declare that "laptop", "phone" and "tablet" are similar words that can be generalized as "mobile":
PUT synonym
{
"settings": {
"index": {
"number_of_shards": 3,
"number_of_replicas": 2,
"analysis": {
"analyzer": {
"synonym": {
"tokenizer": "whitespace",
"filter": [
"synonym"
]
}
},
"filter": {
"synonym": {
"type": "synonym",
"synonyms": [
"phone, tablet, laptop => mobile"
]
}
}
}
}
},
"mappings": {
"synonym" : {
"properties" : {
"field1" : {
"type" : "text",
"analyzer": "synonym",
"search_analyzer": "synonym"
}
}
}
}
}
Now I am creating some docs:
PUT synonym/synonym/1
{
"field1" : "phone"
}
PUT synonym/synonym/2
{
"field1" : "tablet"
}
PUT synonym/synonym/3
{
"field1" : "laptop"
}
Now when I match query for laptop, tablet or phone, the result is always:
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 3,
"successful": 3,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0.2876821,
"hits": [
{
"_index": "synonym",
"_type": "synonym",
"_id": "2",
"_score": 0.2876821,
"_source": {
"field1": "tablet"
}
},
{
"_index": "synonym",
"_type": "synonym",
"_id": "1",
"_score": 0.18232156,
"_source": {
"field1": "phone"
}
},
{
"_index": "synonym",
"_type": "synonym",
"_id": "3",
"_score": 0.18232156,
"_source": {
"field1": "laptop"
}
}
]
}
}
You can see that the score of tablet is always higher even when I search for laptop.
I know that is because I declared them as similar words.
However, I am trying to figure out how can I query so that document with the search term can appear in the first place, before the similar words in the result list.
It can be done by boosting, but there must be a simpler approach..

Answer 1

Multi-fields to your rescue.
Index the field1 in two ways, one with the synonym analyzer, and the other with a standard analyzer.
Now you can simply use a bool-should query to add score for match on field1 (synonym) and on field1.raw (standard).
So, your mappings should be like so:
PUT synonym
{
"settings": {
"index": {
"number_of_shards": 3,
"number_of_replicas": 2,
"analysis": {
"analyzer": {
"synonym": {
"tokenizer": "whitespace",
"filter": [
"synonym"
]
}
},
"filter": {
"synonym": {
"type": "synonym",
"synonyms": [
"phone, tablet, laptop => mobile"
]
}
}
}
}
},
"mappings": {
"synonym": {
"properties": {
"field1": {
"type": "text",
"analyzer": "synonym",
"search_analyzer": "synonym",
"fields": {
"raw": {
"type": "text",
"analyzer": "standard"
}
}
}
}
}
}
}
And you can query using:
GET synonyms/_search?search_type=dfs_query_then_fetch
{
"query": {
"bool": {
"should": [
{
"match": {
"field1": "tablet"
}
},
{
"match": {
"field1.raw": "tablet"
}
}
]
}
}
}
Notice: I've used search_type=dfs_query_then_fetch. Since you're testing on 3 shards and have very few documents, the scores you're getting aren't what they should be. This is because the frequencies are calculated per shard. You can use dfs_query_then_fetch while testing but it is discouraged for production. See: https://www.elastic.co/blog/understanding-query-then-fetch-vs-dfs-query-then-fetch