I Overrrided DefaultSimilarity class to return idf=1 always
Now score is fully dependent on term matching.
If single term is matching, matching docs have same score.
If phrase is matching it has maximum score.
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http://lucene.472066.n3.nabble.com/Identify-exact
I have only pencil scratches yet, can't share it. I can say that i've found
it quite close to approach described there
http://www.ulakha.com/publications.html it's called there "Concept Search",
but as far as I understand I have rather different implementation approach.
On Fri, Oct 5, 2012 at 2:31
absolutely, that's what I didn't get in your initial question. Okay it
seems you are talking about typical eCommerce search problem. I will speak
about it at http://www.apachecon.eu/schedule/presentation/18/ see you.
On Fri, Oct 5, 2012 at 9:47 AM, rhl4tr wrote:
> But user query can contain any
But user query can contain any number of terms. I can not know how many
fields term it has to match.
{
"responseHeader":{
"status":0,
"QTime":1,
"params":{
"mm":"0",
"sort":"score desc",
"indent":"true",
"qf":"exact_keywords",
"wt":"json",
"rows":"
overall task is not clear to me, but if you want to "field's all terms have
matched to user query" i'd suggest to introduce your own Similarity:
- write number of terms as a norm value (which is by default a byte per
doc per field), then
- you'll be able to retrieve this number during search time
