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From Александр Аристов <>
Subject Re[4]: lucene scoring
Date Fri, 08 Aug 2008 09:53:53 GMT
Relevance ranking is an option but we still won't be able compare results. Lets say we have
distributed searching - in this case top 10 from one server is not the same as those which
are from another. Even worse we may get that in the resulting set a document with most top
score is worse than others.

what if we disable normalization or make it constant will results be absolutely dummy?

And anther approach, can we calculate most possible top value? Or just maybe approximation
of it? we then would be able to compare results with it.


-----Original Message-----
From: Grant Ingersoll <>
Date: Thu, 7 Aug 2008 15:54:41 -0400
Subject: Re: Re[2]: lucene scoring

On Aug 7, 2008, at 3:05 PM, Александр Аристов wrote:

> I want implement searching with ability to set so-called a  
> confidence level below which I would treat documents as garbage. I  
> cannot defile the level per query as the level should be relevant  
> for all documents.
> With current scoring implementation the level would mean nothing. I  
> don't believe that since that time (the thread is of 2005year)  
> nothing has been made towards the resolving the issue.

That's because there is no resolution to be had, as far as I know, but  
I'm open to suggestions (patches are even better.)  What would it mean  
to say that a score of 0.5 for "baby kittens" is comparable to a score  
of 0.5 for "death metal"?  Like I said, I don't think that 0.5 for  
"baby kittens" is even comparable later if you added other documents  
that contain any of the query terms.

> Do you think any workarounds like implementing more sophisticated  
> queries so that we have approximately the same normalization values?

I just don't think you will be successful with this, and I don't  
believe it is a Lucene issue alone, but one that applies to all search  
engines, but I could be wrong.

I get what you are trying to do, though, I've wanted to do it from  
time to time.   Another approach may be to look for significant  
differences between scores w/in a result set.   For example, if doc 1  
is 0.8, doc 2 is 0.79 and then doc 3 is 0.2, then maybe one could  
argue that doc 3 is garbage, but even that is somewhat of a stretch.   
Garbage truly is in the eye of the beholder.

Another option is to do more relevance tuning to make sure your top 10  
are as good as possible so that your garbage is minimized.

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