Mailing-List: contact general-help@lucene.apache.org; run by ezmlm
Precedence: bulk
Reply-To: general@lucene.apache.org
Received-SPF: neutral (athena.apache.org: local policy)
Message-ID: <4A375D05.2000601@boozter.com>
Date: Tue, 16 Jun 2009 10:51:17 +0200
From: lionel duboeuf <lionel.duboeuf@boozter.com>
User-Agent: Thunderbird 2.0.0.21 (X11/20090409)
MIME-Version: 1.0
To: general@lucene.apache.org
CC: boozter-tbm@boozter.com
Subject: Re: index per-user basis and document frequency
References: <4A36B7CC.3000108@boozter.com>
 <c7d45fc70906151516w2df19674le5c7d10b014e2175@mail.gmail.com>
In-Reply-To: <c7d45fc70906151516w2df19674le5c7d10b014e2175@mail.gmail.com>
Content-Type: text/plain; charset=UTF-8; format=flowed
Content-Transfer-Encoding: 7bit

Ted Dunning wrote:
> I don't think that this would be such a great idea.
>
> Better to use a custom
> similarity<http://hudson.zones.apache.org/hudson/job/Lucene-trunk/javadoc//org/apache/lucene/search/Similarity.html>data
> structure.  Before you do that, though, you might try just using the
> overall corpus statistics and not worry about this per user indexing with
> specialized statistics.  If users' are no more different from each other
> than sub-corpora in a normal retrieval system then you are liable to get
> much better results using corpus wide stats than with user level stats.
>
> On Mon, Jun 15, 2009 at 2:06 PM, Lionel Duboeuf
> <lionel.duboeuf@boozter.com>wrote:
>   
ok, enven if i modify similarity measure, i will face polysemy problem.
e.g. the term "car" in english is different to the term "car" in french.
Also what is the best approach to calculate easily (and fastly) numDocs 
for a given user ?

thanks for your answer.

lionel