o ask
whether the current default similarity implementation of Lucene is
really BM25, right?
as described at
https://opensourceconnections.com/blog/2015/10/16/bm25-the-next-generation-of-lucene-relevation/
Thanks
Michael
---
don't write anything wrong I
would like to ask
whether the current default similarity implementation of Lucene is
really BM25, right?
as described at
https://opensourceconnections.com/blog/2015/10/16/bm25-the-next-generation-of-lucene-relevation/
Thanks
Mi
> would like to ask
>
> whether the current default similarity implementation of Lucene is
> really BM25, right?
>
> as described at
>
> https://opensourceconnections.com/blog/2015/10/16/bm25-the-next-generation-
Hi
On the Lucene FAQ there is no mentioning re tf-idf or bm25 and I would
like to add some notes, but to be sure I don't write anything wrong I
would like to ask
whether the current default similarity implementation of Lucene is
really BM25, right?
as described at
Hi Siraj,
I think
https://lucene.apache.org/core/6_1_0/core/index.html?org/apache/lucene/search/ConstantScoreQuery.html
should be good enough.
On Fri, Jul 8, 2016 at 12:27 AM Siraj Haider wrote:
> We are in the process of upgrading from 2.x to 6.x. In 2.x we implemented
> our own similarity whe
We are in the process of upgrading from 2.x to 6.x. In 2.x we implemented our
own similarity where all the functions return 1.0f, how can we implement such
thing in 6.x? Is there an implementation already there that we can use and have
the same results?
--
Regards
-Siraj Haider
(212) 306-01
Hi Luis,
Thats an interesting question. Can you share your similarity?
I suspect you return 1 expect Similarity#coord method.
Not sure but, for phrase query, one may require to modify
ExactPhraseScorer/ExactPhraseScorer etc.
ahmet
On Thursday, May 12, 2016 5:41 AM, Luís Filipe Nassif
wrote:
Hi,
In the past (lucene 4) I have tried to implement a simple Similarity to
only count the number of occurrences (term frequencies) into the documents,
ignoring norms, doc frequencies, boosts... It worked for some queries like
term and wildcard queries, but not for others, like phrase and range
qu
d "idf".
>
> FYI: I could implement "idf" according to miisliat.com formula, but not
> the
> "tf" and "norm"
>
> Could you please comment me how I can implement a new Similarity class
> that
> will fit in the Lucene's architecture
>>> Try this as an example:
>>>
>>> Setup a really simple index with 1 or 2 docs each with a few words.
>>> Setup a simple Similarity class where you override all of these
>>> methods to return 1 (or some
ext:
http://www.nabble.com/Vector-Space-Model%3A-New-Similarity-Implementation-Issues-tp15696719p15745822.html
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-
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t trying to understand Lucene at an academic/programming level or
> do you have something you are trying to achieve in terms of relevance?
>
> -Grant
>
> -
&g
On Feb 28, 2008, at 9:00 AM, Dharmalingam wrote:
Thanks for the reply. Sorry if my explanation is not clear. Yes, you
are
correct the model is based on Salton's VSM. However, the
calculation of the
term weight and the doc norm is, in my opinion, different from
Lucene. If
you look at th
Next Training: April 7, 2008 at ApacheCon Europe in Amsterdam
>
> Lucene Helpful Hints:
> http://wiki.apache.org/lucene-java/BasicsOfPerformance
> http://wiki.apache.org/lucene-java/LuceneFAQ
>
>
>
>
>
>
Not sure I am understanding what you are asking, but I will give it a
shot. See below
On Feb 26, 2008, at 3:45 PM, Dharmalingam wrote:
Hi List,
I am pretty new to Lucene. Certainly, it is very exciting. I need to
implement a new Similarity class based on the Term Vector Space
Model giv
--
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Sorry, the image wasn't sent:
http://wwwhome.cs.utwente.nl/~trieschn/bm25.PNG
> -Original Message-
> From: Trieschnigg, R.B. (Dolf)
> [mailto:[EMAIL PROTECTED]
> Sent: vrijdag 17 februari 2006 10:54
> To: java-user@lucene.apache.org
> Subject: RE: BM25 Si
> > I would like to implement the Okapi BM25 weighting function
> > using my own Similarity implementation. Unfortunately BM25
> > requires the document length in the score calculation, which
> > is not provided by the Scorer.
>
> How do you want to measure docu
Trieschnigg, R.B. (Dolf) wrote:
I would like to implement the Okapi BM25 weighting function using my own
Similarity implementation. Unfortunately BM25 requires the document length in
the score calculation, which is not provided by the Scorer.
How do you want to measure document length? If
Hi,
I would like to implement the Okapi BM25 weighting function using my own
Similarity implementation. Unfortunately BM25 requires the document length in
the score calculation, which is not provided by the Scorer.
Does anyone know a solution to this problem?
I've tried to find
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