I've a set of documents annotated with hierarchial taxonomy tags, E.g.
[
{
"id": 1,
"title": "a funny book",
"authors": ["Jean Bon", "Alex Terieur"],
"book_category": "/novel/comedy/new"
},
{
"id": 2,
"title": "a dramatic book",
"authors": ["Alex Terieur"],
"book_category": "/novel/drama"
},
{
"id": 3,
"title": "A hilarious book",
"authors": ["Marc Assin", "Harry Covert"],
"book_category": "/novel/comedy"
},
{
"id": 4,
"title": "A sad story",
"authors": ["Gerard Menvusa", "Alex Terieur"],
"book_category": "/novel/drama"
},
{
"id": 5,
"title": "A very sad story",
"authors": ["Gerard Menvusa", "Alain Terieur"],
"book_category": "/novel"
}]
I need to search book by "book_category". The search must return books that
match the query category exactly or partially (with a defined depth
threshold) and give them a different score in function of the match degree.
E.g.: query "book_category=/novel/comedy" and "depth_threshold=1" must
return books with book_category=/novel/comedy (score=100%), /novel and
/novel/comedy/new (score < 100%).
I tried the TopScoreDocCollector in the search, but it returns the book
which book_category at least contains the query category, and gives them the
same score.
How can i obtain this search function that returns also the more general
category and gives different match scores to the results?
P.S.: i don't need a faced search.
Thanks
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