hi!
I am trying to do something a little unique...
I have a 90k text documents that I am trying to search
Search A: indexes and searches the documents using regular relevancy search
Search B: indexes and searches the documents using a smaller subset of "key"
words that I have chosen
This gives
(bump) - any thoughts?
theDude_2 wrote:
>
> hi!
>
> I am trying to do something a little unique...
>
> I have a 90k text documents that I am trying to search
> Search A: indexes and searches the documents using regular relevancy
> search
> Search B: indexes and searches the documents us
I'd start by doing some research on the question rather than asking for a
solution..
What your asking for can be considered 'Federated Search'
http://en.wikipedia.org/wiki/Federated_search
And it can be conceived in as many ways as you have document types. Any
answer will probably end up
customize
I appreciate your response, and read the wiki article concerning the
Federated search
and
I'm not sure that my project falls into the "Federated Search" bucket...
What I've done is created 2 indexes created with the same documents.
One index, contains the full documents - great for pure relevanc
*Edit: each indexed text document contains a related field for identification
purposes, so I would be able to identify the scores for both indexes through
this field*
theDude_2 wrote:
>
> I appreciate your response, and read the wiki article concerning the
> Federated search
> and
>
> I'm not
Why not put the keywords into the same document as another field? and search
both fields
at once, you can then use lucene syntax to give a boosting to the keyword
fields.
e.g.
body:A good game last night by the redskins
keyword: redskins
Query= body:(game OR redskins) keyword:(game OR redskins)^10
Ah, Interesting... I didnt think of that! I will try it and report back
pjaol wrote:
>
> Why not put the keywords into the same document as another field? and
> search
> both fields
> at once, you can then use lucene syntax to give a boosting to the keyword
> fields.
> e.g.
> body:A good game
If you can build an analyzer that tokenizes the second field so that it
filters out the words you don't want, you can then take advantage of
more intelligent queries as well.
So for the example that pjaol wrote, the query would become something
like this:
Query= body:(game OR redskins) keyw
Erm, I likely should have mentioned that this technique requires the use
of a MultiFieldQueryParser.
Matt
Matthew Hall wrote:
If you can build an analyzer that tokenizes the second field so that
it filters out the words you don't want, you can then take advantage
of more intelligent queries a
Thanks!
I wound up indexing both versions in the same index, and boosting the words
that appeared in the "good word" list!
Thanks again for your advice!
Matthew Hall-7 wrote:
>
> Erm, I likely should have mentioned that this technique requires the use
> of a MultiFieldQueryParser.
>
> Matt
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