Hello,
--- Chakra Yadavalli <[EMAIL PROTECTED]> wrote:
> Hello, I am not sure if this is the right question for this list but
> it is in regards to search engines.
This is not really the right place to ask these types of questions,
but... robots at mccmedia.com may be a better place to ask, or o
Hello, I am not sure if this is the right question for this list but
it is in regards to search engines.
Suppose you have a website that hosts some protected content that is
accessible via registered users. How you make the content searchable
by Google and other popular websearch engines? The idea
The Snowball stemmers are generated from the definitions pulled
automatically from the Snowball projects CVS server.
I just tried regenerating, which automatically pulls from CVS, and got
this error:
compile-compiler:
[apply]
/Users/erik/dev/lucene/java/contrib/snowball/snowball/website
Hi
I found a problem with the SpanishStemmer in SnowballAnalyzer.
The words finished in "ismo" are striped fine, but words finished in
"guismo" not.
in Spanish:
"america" and "americanismo" are fine
"argentina" and "argentinismo" are fine
"amigo" is fine but "amigismo" not is fine
the right word
The reason your suggestion is not practical is scalability. In a production
environment you might have, for example, 10,000 stored queries and 10 new
documents a minute. That's a fair bit of load on the system for only one
aspect of a much larger search application.
On Wed, 16 Mar 2005, Dan Funk
On Wednesday 16 March 2005 18:26, Robert Watkins wrote:
> We are considering Lucene as a replacement for Verity K2 (I won't go
> into the myriad reasons, other than to highlight that the K2 Java API
> is riddled with errors, falsities and just plain stupidity [okay,
> I've had my rant]) and figure
I don't understand - this is all happening in the background right?
Why not just add the document to the index, then execute all the queries
(with an extra clause to restrict results to that document) and see what
hits?
Robert Watkins wrote:
Okay, I only bought your book a few days ago, so I ha
Okay, I only bought your book a few days ago, so I haven't read much
yet! Also, this project is still at the exploratory level, so very
little time has been dedicated to it (the irony is I am currently
spending most of my time trying to work around K2 ... issues). As
such, it will be some time befo
I think this is doable. Lucene compares how similar query terms are to
terms in indexed documents. Flip that around, and you are close to a
solution. Perhaps you'll want to process incoming documents to keep
only the top N most-important terms or phrases. You could then create
a query out of th
We are considering Lucene as a replacement for Verity K2 (I won't go
into the myriad reasons, other than to highlight that the K2 Java API
is riddled with errors, falsities and just plain stupidity [okay,
I've had my rant]) and figure that Lucene can do what we are
currently using K2 for, except fo
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