Hi,
I was wondering whether there is a way I can feed additional text (from a document) to get more accurate results?
For example, a user can upload a PDF that contains text that s/he thinks is relevant to the search. Then use something like TF-IDF to extract important words and feed them to something like a should
query along with the actual query in a must
query. Has anyone tried something like this? Has it worked? Any better way to achieve this?
Yes @Christian_Dahlqvist But can I use it along with a user entered query? I believe this is the query you are referring to:
GET /_search
{
"query": {
"more_like_this" : {
"fields" : ["name.first", "name.last"],
"like" : [
{
"_index" : "marvel",
"doc" : {
"name": {
"first": "Ben",
"last": "Grimm"
},
"_doc": "You got no idea what I'd... what I'd give to be invisible."
}
},
{
"_index" : "marvel",
"_id" : "2"
}
],
"min_term_freq" : 1,
"max_query_terms" : 12
}
}
}
I understand the part of feeding in the artificial document, but I want to combine that with a user-entered query. Where do I put that?
I am not sure it will get you where you want, but can’t you wrap this query and the user query in a Boolean query?
Something like the user query in a must
clause and the extra keywords in a should
clause?
Yes, something like that could potentially work.
This topic was automatically closed 28 days after the last reply. New replies are no longer allowed.