Elasticsearch as a solution for automapping different data - elasticsearch

Question

This is a tricky one.
I'm currently working in a travel agency that needs to map its hotels to other agencies hotels. So let's say that we got an hotel like this one:
Code123, Hotel name 123, street 123, postcode132, country123
And we want to map it to other hotel that is:
ACode123, Hotel 123 name, st 123, pc132, country123
Regarding this, I want to ask two questions:
Is elasticsearch a good solution for this case? So far, I've gotten some good results thanks to elasticsearch nice features regarding search but I've also gotten some misleading matches (for instance, when having long addresses that should match with short addresses).
The other one is, if it's a good solution, which approach should I take?
To give you more context, this is what I got so far:
{
"query": {
"bool": {
"must": [
{
"bool": {
"must": [
{
"bool": {
"must": [
{
"bool": {
"must": [
{
"bool": {
"must": [
{
"bool": {
"must": [
{
"bool": {
"must": [
{
"query_string": {
"default_field": "name",
"query": "Holiday~ Inn~ Express~ Tianjin~ ",
"fuzzy_min_sim": 0.9
}
}
]
}
}
],
"should": [
{
"filtered": {
"query": {
"bool": {
"must": [
{
"match": {
"name": {
"query": "Holiday Inn Express Tianjin",
"boost": 1
}
}
},
{
"query_string": {
"default_field": "country",
"query": "CHINA~ ",
"fuzzy_min_sim": 0.9
}
}
],
"should": [
{
"wildcard": {
"nameTerm": {
"wildcard": "*Holiday* Inn*",
"boost": 1
}
}
}
]
}
},
"filter": {
"geo_distance": {
"distance": "2000m",
"coordinates": {
"lon": 117.1852,
"lat": 39.12841
}
}
}
}
}
]
}
}
],
"should": [
{
"filtered": {
"query": {
"bool": {
"must": [
{
"match": {
"name": {
"query": "Holiday Inn Express Tianjin",
"boost": 1
}
}
},
{
"query_string": {
"default_field": "country",
"query": "CHINA~ ",
"fuzzy_min_sim": 0.9
}
}
],
"should": [
{
"wildcard": {
"nameTerm": {
"wildcard": "*Holiday* Inn* Express*",
"boost": 1.5
}
}
}
]
}
},
"filter": {
"geo_distance": {
"distance": "1500m",
"coordinates": {
"lon": 117.1852,
"lat": 39.12841
}
}
}
}
}
]
}
}
],
"should": [
{
"filtered": {
"query": {
"bool": {
"must": [
{
"match": {
"name": {
"query": "Holiday Inn Express Tianjin",
"boost": 1
}
}
},
{
"query_string": {
"default_field": "country",
"query": "CHINA~ ",
"fuzzy_min_sim": 0.9
}
}
],
"should": [
{
"query_string": {
"default_field": "addressNoNumbers",
"query": " ZHONGSHAN ROAD HEBEI DISTRICT",
"fuzzy_min_sim": 0.8
}
},
{
"match": {
"addressNumbers": {
"query": "288",
"boost": 1.5
}
}
},
{
"term": {
"nameTerm": {
"value": "Holiday Inn Express Tianjin",
"boost": 2
}
}
}
]
}
},
"filter": {
"geo_distance": {
"distance": "1000m",
"coordinates": {
"lon": 117.1852,
"lat": 39.12841
}
}
}
}
}
]
}
}
],
"should": [
{
"filtered": {
"query": {
"bool": {
"must": [
{
"match": {
"name": {
"query": "Holiday Inn Express Tianjin",
"boost": 1
}
}
}
],
"should": [
{
"match": {
"addressNumbers": {
"query": "288",
"boost": 1.5
}
}
},
{
"wildcard": {
"addressTerm": {
"wildcard": "*ZHONGSHAN* ROAD*",
"boost": 1
}
}
},
{
"term": {
"nameTerm": {
"value": "Holiday Inn Express Tianjin",
"boost": 2
}
}
}
]
}
},
"filter": {
"geo_distance": {
"distance": "500m",
"coordinates": {
"lon": 117.1852,
"lat": 39.12841
}
}
}
}
}
]
}
}
],
"should": [
{
"filtered": {
"query": {
"bool": {
"must": [
{
"match": {
"name": {
"query": "Holiday Inn Express Tianjin",
"boost": 1
}
}
}
],
"should": [
{
"match": {
"addressNumbers": {
"query": "288",
"boost": 1.5
}
}
},
{
"wildcard": {
"addressTerm": {
"wildcard": "*ZHONGSHAN* ROAD*",
"boost": 1
}
}
},
{
"term": {
"nameTerm": {
"value": "Holiday Inn Express Tianjin",
"boost": 2
}
}
}
]
}
},
"filter": {
"geo_distance": {
"distance": "300m",
"coordinates": {
"lon": 117.1852,
"lat": 39.12841
}
}
}
}
}
]
}
}
],
"should": [
{
"filtered": {
"query": {
"bool": {
"must": [
{
"match": {
"name": {
"query": "Holiday Inn Express Tianjin",
"boost": 1
}
}
}
],
"should": [
{
"match": {
"addressNumbers": {
"query": "288",
"boost": 1.5
}
}
},
{
"wildcard": {
"addressTerm": {
"wildcard": "*ZHONGSHAN* ROAD*",
"boost": 1
}
}
},
{
"term": {
"nameTerm": {
"value": "Holiday Inn Express Tianjin",
"boost": 2
}
}
}
]
}
},
"filter": {
"geo_distance": {
"distance": "100m",
"coordinates": {
"lon": 117.1852,
"lat": 39.12841
}
}
}
}
}
]
}
}
}
So lots of nesting, that work quite well when I'm getting all the fields but not that much when I'm missing coordinate.
But anyway, my main concern is if I should go with elasticsearch or not (and which could be the alternative!)
Thanks in advance!