Chuck Williams wrote:
I believe the biggest problem with Lucene's approach relative to the pure vector space model is that Lucene does not properly normalize. The pure vector space model implements a cosine in the strictly positive sector of the coordinate space. This is guaranteed intrinsically
: I question whether such scores are more meaningful. Yes, such scores
: would be guaranteed to be between zero and one, but would 0.8 really be
: meaningful? I don't think so. Do you have pointers to research which
: demonstrates this? E.g., when such a scoring method is used, that
:
There is one case that I can think of where this 'constant' scoring
would be useful, and I think Chuck already mentioned this 1-2 months
ago. For instace, having such scores would allow one to create alert
applications where queries run by some scheduler would trigger an alert
whenever the score
: A question about scoring function in Lucene
Chris Hostetter wrote:
For example, using the current scoring equation, if i do a search
for
Doug Cutting and the results/scores i get back are...
1: 0.9
2: 0.3
3: 0.21
4: 0.21
5: 0.1
.
Chuck
-Original Message-
From: Vikas Gupta [mailto:[EMAIL PROTECTED]
Sent: Tuesday, December 14, 2004 9:32 PM
To: Lucene Users List
Subject: Re: A question about scoring function
in Lucene
Lucene uses the vector space model. To
understand
15, 2004 1:18 AM
To: Lucene Users List
Subject: RE: A question about scoring function in Lucene
Thank for your answer,
In Lucene scoring function, they use only norm_q,
but for one query, norm_q is the same for all
documents.
So norm_q is actually not effect the score
Otis Gospodnetic wrote:
There is one case that I can think of where this 'constant' scoring
would be useful, and I think Chuck already mentioned this 1-2 months
ago. For instace, having such scores would allow one to create alert
applications where queries run by some scheduler would trigger an
Chris Hostetter wrote:
For example, using the current scoring equation, if i do a search for
Doug Cutting and the results/scores i get back are...
1: 0.9
2: 0.3
3: 0.21
4: 0.21
5: 0.1
...then there are at least two meaningful pieces of data I can glean:
]
Sent: Tuesday, December 14, 2004 9:32 PM
To: Lucene Users List
Subject: Re: A question about scoring function in Lucene
Lucene uses the vector space model. To understand that:
-Read section 2.1 of Space optimizations for Total Ranking paper
(Linked
here http
Lucene uses the vector space model. To understand that:
-Read section 2.1 of Space optimizations for Total Ranking paper (Linked
here http://lucene.sourceforge.net/publications.html)
-Read section 6 to 6.4 of
http://www.csee.umbc.edu/cadip/readings/IR.report.120600.book.pdf
-Read section 1 of
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