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https://issues.apache.org/jira/browse/LUCENE-3220?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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David Mark Nemeskey updated LUCENE-3220:
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Attachment: LUCENE-3220.patch
Implementation of the DFR framework added. Lots of nocommits, though. I things
to think about:
* lots of (float) conversions. Maybe the inner API (BasicModel, etc.) could
use doubles? According to my experience, double is faster anyway, at least on
64bit architectures
* I am not overly happy about the naming scheme, i.e. BasicModelBE, etc. Maybe
we should do it the same way as in Terrier, with a basicmodel package and class
names like BE?
* A regular SimilarityProvider implementation won't play well with
DFRSimilarity, in case the user wants to use several different setups.
Actually, this is a problem for all similarities that have parameters (e.g.
BM25 with b and k).
Also, I think we need that NormConverter we talked earlier on irc, so that the
Similarities can run on any index.
> Implement various ranking models as Similarities
> ------------------------------------------------
>
> Key: LUCENE-3220
> URL: https://issues.apache.org/jira/browse/LUCENE-3220
> Project: Lucene - Java
> Issue Type: Sub-task
> Components: core/search
> Affects Versions: flexscoring branch
> Reporter: David Mark Nemeskey
> Assignee: David Mark Nemeskey
> Labels: gsoc
> Attachments: LUCENE-3220.patch, LUCENE-3220.patch, LUCENE-3220.patch,
> LUCENE-3220.patch, LUCENE-3220.patch, LUCENE-3220.patch
>
> Original Estimate: 336h
> Remaining Estimate: 336h
>
> With [LUCENE-3174|https://issues.apache.org/jira/browse/LUCENE-3174] done, we
> can finally work on implementing the standard ranking models. Currently DFR,
> BM25 and LM are on the menu.
> TODO:
> * {{EasyStats}}: contains all statistics that might be relevant for a
> ranking algorithm
> * {{EasySimilarity}}: the ancestor of all the other similarities. Hides the
> DocScorers and as much implementation detail as possible
> * _BM25_: the current "mock" implementation might be OK
> * _LM_
> * _DFR_
> Done:
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