Scoring higher for shorter fields - elasticsearch

Question

I'm trying to get a higher score (or at least the same score) for the shortest values on Elastic Search.
Let's say I have these documents: "Abc", "Abca", "Abcb", "Abcc". The field label.ngram uses an EdgeNgram analyser.
With a really simple query like that:
{
"query": {
"match": {
"label.ngram": {
"query": "Ab"
}
}
}
}
I always get first the documents "Abca", "Abcb", "Abcc" instead of "Abc".
How can I get "Abc" first?
(should I use this: https://www.elastic.co/guide/en/elasticsearch/reference/current/index-modules-similarity.html?)
Thanks!

Answer 1

This is happening due to field normalization and to get the same score, you have to disable the norms on the field.
Norms store various normalization factors that are later used at query
time in order to compute the score of a document relatively to a
query.
Adding a working example with index data, mapping, search query, and search result
Index Mapping:
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "my_tokenizer"
}
},
"tokenizer": {
"my_tokenizer": {
"type": "edge_ngram",
"min_gram": 2,
"max_gram": 10,
"token_chars": [
"letter",
"digit"
]
}
}
}
},
"mappings": {
"properties": {
"title": {
"type": "text",
"norms": false,
"analyzer": "my_analyzer"
}
}
}
}
Index Data:
{
"title": "Abca"
}
{
"title": "Abcb"
}
{
"title": "Abcc"
}
{
"title": "Abc"
}
Search Query:
{
"query": {
"match": {
"title": {
"query": "Ab"
}
}
}
}
Search Result:
"hits": [
{
"_index": "65953349",
"_type": "_doc",
"_id": "1",
"_score": 0.1424427,
"_source": {
"title": "Abca"
}
},
{
"_index": "65953349",
"_type": "_doc",
"_id": "2",
"_score": 0.1424427,
"_source": {
"title": "Abcb"
}
},
{
"_index": "65953349",
"_type": "_doc",
"_id": "3",
"_score": 0.1424427,
"_source": {
"title": "Abcc"
}
},
{
"_index": "65953349",
"_type": "_doc",
"_id": "4",
"_score": 0.1424427,
"_source": {
"title": "Abc"
}
}
]

Answer 2

As mentioned by #ESCoder that using norms you can fix the scoring but this would not be very useful, if you want to score your search results, as this would cause all the documents in your search results to have the same score, which will impact the relevance of your search results big time.
Maybe you should tweak the document length norm param for default similarity algorithm(BM25) if you are on ES 5.X or higher. I tried doing this with your dataset and my setting but didn't make it to work.
Second option which will mostly work as suggested by you is to store the size of your fields in different field(but) this you should populate from your application as after analysis process, various tokens would be generated for same field. but this is extra overhead and I would prefer doing this by tweaking the similarity algo param.