[jira] Updated: (LUCENE-1124) short circuit FuzzyQuery.rewrite when input token length is small compared to minSimilarity
[
https://issues.apache.org/jira/browse/LUCENE-1124?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael McCandless updated LUCENE-1124:
---
Attachment: LUCENE-1124.patch
Attach patch (based on 2.9) showing the bug, along with the fix. Instead of
rewriting to empty BooleanQuery when prefix term is not long enough, I rewrite
to TermQuery with that prefix. This way the exact term matches.
I'll commit shortly to trunk 2.9.x.
short circuit FuzzyQuery.rewrite when input token length is small compared to
minSimilarity
---
Key: LUCENE-1124
URL: https://issues.apache.org/jira/browse/LUCENE-1124
Project: Lucene - Java
Issue Type: Improvement
Components: Query/Scoring
Reporter: Hoss Man
Assignee: Mark Miller
Priority: Trivial
Fix For: 2.9
Attachments: LUCENE-1124.patch, LUCENE-1124.patch, LUCENE-1124.patch,
LUCENE-1124.patch
I found this (unreplied to) email floating around in my Lucene folder from
during the holidays...
{noformat}
From: Timo Nentwig
To: java-dev
Subject: Fuzzy makes no sense for short tokens
Date: Mon, 31 Dec 2007 16:01:11 +0100
Message-Id: 200712311601.12255.luc...@nitwit.de
Hi!
it generally makes no sense to search fuzzy for short tokens because changing
even only a single character of course already results in a high edit
distance. So it actually only makes sense in this case:
if( token.length() 1f / (1f - minSimilarity) )
E.g. changing one character in a 3-letter token (foo) results in an edit
distance of 0.6. And if minSimilarity (which is by default: 0.5 :-) is higher
we can save all the expensive rewrite() logic.
{noformat}
I don't know much about FuzzyQueries, but this reasoning seems sound ...
FuzzyQuery.rewrite should be able to completely skip all TermEnumeration in
the event that the input token is shorter then some simple math on the
minSimilarity. (i'm not smart enough to be certain that the math above is
right however ... it's been a while since i looked at Levenstein distances
... tests needed)
--
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[jira] Updated: (LUCENE-1124) short circuit FuzzyQuery.rewrite when input token length is small compared to minSimilarity
[
https://issues.apache.org/jira/browse/LUCENE-1124?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael McCandless updated LUCENE-1124:
---
Fix Version/s: (was: 2.9)
3.0
2.9.1
short circuit FuzzyQuery.rewrite when input token length is small compared to
minSimilarity
---
Key: LUCENE-1124
URL: https://issues.apache.org/jira/browse/LUCENE-1124
Project: Lucene - Java
Issue Type: Improvement
Components: Query/Scoring
Reporter: Hoss Man
Assignee: Mark Miller
Priority: Trivial
Fix For: 2.9.1, 3.0
Attachments: LUCENE-1124.patch, LUCENE-1124.patch, LUCENE-1124.patch,
LUCENE-1124.patch
I found this (unreplied to) email floating around in my Lucene folder from
during the holidays...
{noformat}
From: Timo Nentwig
To: java-dev
Subject: Fuzzy makes no sense for short tokens
Date: Mon, 31 Dec 2007 16:01:11 +0100
Message-Id: 200712311601.12255.luc...@nitwit.de
Hi!
it generally makes no sense to search fuzzy for short tokens because changing
even only a single character of course already results in a high edit
distance. So it actually only makes sense in this case:
if( token.length() 1f / (1f - minSimilarity) )
E.g. changing one character in a 3-letter token (foo) results in an edit
distance of 0.6. And if minSimilarity (which is by default: 0.5 :-) is higher
we can save all the expensive rewrite() logic.
{noformat}
I don't know much about FuzzyQueries, but this reasoning seems sound ...
FuzzyQuery.rewrite should be able to completely skip all TermEnumeration in
the event that the input token is shorter then some simple math on the
minSimilarity. (i'm not smart enough to be certain that the math above is
right however ... it's been a while since i looked at Levenstein distances
... tests needed)
--
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You can reply to this email to add a comment to the issue online.
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[jira] Updated: (LUCENE-1124) short circuit FuzzyQuery.rewrite when input token length is small compared to minSimilarity
[
https://issues.apache.org/jira/browse/LUCENE-1124?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mark Miller updated LUCENE-1124:
Attachment: LUCENE-1124.patch
Updated to trunk.
Im going to commit in few days if no one objects.
short circuit FuzzyQuery.rewrite when input token length is small compared to
minSimilarity
---
Key: LUCENE-1124
URL: https://issues.apache.org/jira/browse/LUCENE-1124
Project: Lucene - Java
Issue Type: Improvement
Components: Query/Scoring
Reporter: Hoss Man
Attachments: LUCENE-1124.patch, LUCENE-1124.patch, LUCENE-1124.patch
I found this (unreplied to) email floating around in my Lucene folder from
during the holidays...
{noformat}
From: Timo Nentwig
To: java-dev
Subject: Fuzzy makes no sense for short tokens
Date: Mon, 31 Dec 2007 16:01:11 +0100
Message-Id: 200712311601.12255.luc...@nitwit.de
Hi!
it generally makes no sense to search fuzzy for short tokens because changing
even only a single character of course already results in a high edit
distance. So it actually only makes sense in this case:
if( token.length() 1f / (1f - minSimilarity) )
E.g. changing one character in a 3-letter token (foo) results in an edit
distance of 0.6. And if minSimilarity (which is by default: 0.5 :-) is higher
we can save all the expensive rewrite() logic.
{noformat}
I don't know much about FuzzyQueries, but this reasoning seems sound ...
FuzzyQuery.rewrite should be able to completely skip all TermEnumeration in
the event that the input token is shorter then some simple math on the
minSimilarity. (i'm not smart enough to be certain that the math above is
right however ... it's been a while since i looked at Levenstein distances
... tests needed)
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
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To unsubscribe, e-mail: java-dev-unsubscr...@lucene.apache.org
For additional commands, e-mail: java-dev-h...@lucene.apache.org
[jira] Updated: (LUCENE-1124) short circuit FuzzyQuery.rewrite when input token length is small compared to minSimilarity
[
https://issues.apache.org/jira/browse/LUCENE-1124?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mark Miller updated LUCENE-1124:
Fix Version/s: 2.9
Assignee: Mark Miller
short circuit FuzzyQuery.rewrite when input token length is small compared to
minSimilarity
---
Key: LUCENE-1124
URL: https://issues.apache.org/jira/browse/LUCENE-1124
Project: Lucene - Java
Issue Type: Improvement
Components: Query/Scoring
Reporter: Hoss Man
Assignee: Mark Miller
Fix For: 2.9
Attachments: LUCENE-1124.patch, LUCENE-1124.patch, LUCENE-1124.patch
I found this (unreplied to) email floating around in my Lucene folder from
during the holidays...
{noformat}
From: Timo Nentwig
To: java-dev
Subject: Fuzzy makes no sense for short tokens
Date: Mon, 31 Dec 2007 16:01:11 +0100
Message-Id: 200712311601.12255.luc...@nitwit.de
Hi!
it generally makes no sense to search fuzzy for short tokens because changing
even only a single character of course already results in a high edit
distance. So it actually only makes sense in this case:
if( token.length() 1f / (1f - minSimilarity) )
E.g. changing one character in a 3-letter token (foo) results in an edit
distance of 0.6. And if minSimilarity (which is by default: 0.5 :-) is higher
we can save all the expensive rewrite() logic.
{noformat}
I don't know much about FuzzyQueries, but this reasoning seems sound ...
FuzzyQuery.rewrite should be able to completely skip all TermEnumeration in
the event that the input token is shorter then some simple math on the
minSimilarity. (i'm not smart enough to be certain that the math above is
right however ... it's been a while since i looked at Levenstein distances
... tests needed)
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
-
To unsubscribe, e-mail: java-dev-unsubscr...@lucene.apache.org
For additional commands, e-mail: java-dev-h...@lucene.apache.org
[jira] Updated: (LUCENE-1124) short circuit FuzzyQuery.rewrite when input token length is small compared to minSimilarity
[
https://issues.apache.org/jira/browse/LUCENE-1124?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Mark Miller updated LUCENE-1124:
Priority: Trivial (was: Major)
short circuit FuzzyQuery.rewrite when input token length is small compared to
minSimilarity
---
Key: LUCENE-1124
URL: https://issues.apache.org/jira/browse/LUCENE-1124
Project: Lucene - Java
Issue Type: Improvement
Components: Query/Scoring
Reporter: Hoss Man
Assignee: Mark Miller
Priority: Trivial
Fix For: 2.9
Attachments: LUCENE-1124.patch, LUCENE-1124.patch, LUCENE-1124.patch
I found this (unreplied to) email floating around in my Lucene folder from
during the holidays...
{noformat}
From: Timo Nentwig
To: java-dev
Subject: Fuzzy makes no sense for short tokens
Date: Mon, 31 Dec 2007 16:01:11 +0100
Message-Id: 200712311601.12255.luc...@nitwit.de
Hi!
it generally makes no sense to search fuzzy for short tokens because changing
even only a single character of course already results in a high edit
distance. So it actually only makes sense in this case:
if( token.length() 1f / (1f - minSimilarity) )
E.g. changing one character in a 3-letter token (foo) results in an edit
distance of 0.6. And if minSimilarity (which is by default: 0.5 :-) is higher
we can save all the expensive rewrite() logic.
{noformat}
I don't know much about FuzzyQueries, but this reasoning seems sound ...
FuzzyQuery.rewrite should be able to completely skip all TermEnumeration in
the event that the input token is shorter then some simple math on the
minSimilarity. (i'm not smart enough to be certain that the math above is
right however ... it's been a while since i looked at Levenstein distances
... tests needed)
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
-
To unsubscribe, e-mail: java-dev-unsubscr...@lucene.apache.org
For additional commands, e-mail: java-dev-h...@lucene.apache.org
[jira] Updated: (LUCENE-1124) short circuit FuzzyQuery.rewrite when input token length is small compared to minSimilarity
[
https://issues.apache.org/jira/browse/LUCENE-1124?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Otis Gospodnetic updated LUCENE-1124:
-
Summary: short circuit FuzzyQuery.rewrite when input token length is small
compared to minSimilarity (was: short circuit FuzzyQuery.rewrite when input
okenlengh is small compared to minSimilarity)
short circuit FuzzyQuery.rewrite when input token length is small compared to
minSimilarity
---
Key: LUCENE-1124
URL: https://issues.apache.org/jira/browse/LUCENE-1124
Project: Lucene - Java
Issue Type: Improvement
Components: Query/Scoring
Reporter: Hoss Man
Attachments: LUCENE-1124.patch, LUCENE-1124.patch
I found this (unreplied to) email floating around in my Lucene folder from
during the holidays...
{noformat}
From: Timo Nentwig
To: java-dev
Subject: Fuzzy makes no sense for short tokens
Date: Mon, 31 Dec 2007 16:01:11 +0100
Message-Id: [EMAIL PROTECTED]
Hi!
it generally makes no sense to search fuzzy for short tokens because changing
even only a single character of course already results in a high edit
distance. So it actually only makes sense in this case:
if( token.length() 1f / (1f - minSimilarity) )
E.g. changing one character in a 3-letter token (foo) results in an edit
distance of 0.6. And if minSimilarity (which is by default: 0.5 :-) is higher
we can save all the expensive rewrite() logic.
{noformat}
I don't know much about FuzzyQueries, but this reasoning seems sound ...
FuzzyQuery.rewrite should be able to completely skip all TermEnumeration in
the event that the input token is shorter then some simple math on the
minSimilarity. (i'm not smart enough to be certain that the math above is
right however ... it's been a while since i looked at Levenstein distances
... tests needed)
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
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To unsubscribe, e-mail: [EMAIL PROTECTED]
For additional commands, e-mail: [EMAIL PROTECTED]
