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Nov 6, 2009, 10:38 AM
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[jira] Issue Comment Edited: (LUCENE-1812) Static index pruning by in-document term frequency (Carmel pruning)
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[ https://issues.apache.org/jira/browse/LUCENE-1812?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12774355#action_12774355 ]
Steven Rowe edited comment on LUCENE-1812 at 11/6/09 6:36 PM:
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Andzrej, when I try to look at [the PDF you posted|http://wiki.apache.org/lucene-java/StaticIndexPruning?action=AttachFile&do=get&target=pruning.pdf] on [the StaticIndexPruning wiki page|http://wiki.apache.org/lucene-java/StaticIndexPruning], Adobe Acrobats gives me the following error:
{quote}
Cannot extract the embedded font 'CAAAA+ArialMT'. Some characters may not display or print correctly.
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and the text is illegible - everything except the page titles looks like a series of dots.
was (Author: steve_rowe):
Andzrej, when I try to look at [the PDF you posted|http://wiki.apache.org/lucene-java/StaticIndexPruning?action=AttachFile&do=get&target=pruning.pdf] on [the StaticIndexPruning wiki page|http://wiki.apache.org/lucene-java/StaticIndexPruning] wiki page, Adobe Acrobats gives me the following error:
{quote}
Cannot extract the embedded font 'CAAAA+ArialMT'. Some characters may not display or print correctly.
{quote}
and the text is illegible - everything except the page titles looks like a series of dots.
> Static index pruning by in-document term frequency (Carmel pruning)
> -------------------------------------------------------------------
>
> Key: LUCENE-1812
> URL: https://issues.apache.org/jira/browse/LUCENE-1812
> Project: Lucene - Java
> Issue Type: New Feature
> Components: contrib/*
> Affects Versions: 2.9
> Reporter: Andrzej Bialecki
> Attachments: pruning.patch, pruning.patch
>
>
> This module provides tools to produce a subset of input indexes by removing postings data for those terms where their in-document frequency is below a specified threshold. The net effect of this processing is a much smaller index that for common types of queries returns nearly identical top-N results as compared with the original index, but with increased performance.
> Optionally, stored values and term vectors can also be removed. This functionality is largely independent, so it can be used without term pruning (when term freq. threshold is set to 1).
> As the threshold value increases, the total size of the index decreases, search performance increases, and recall decreases (i.e. search quality deteriorates). NOTE: especially phrase recall deteriorates significantly at higher threshold values.
> Primary purpose of this class is to produce small first-tier indexes that fit completely in RAM, and store these indexes using IndexWriter.addIndexes(IndexReader[]). Usually the performance of this class will not be sufficient to use the resulting index view for on-the-fly pruning and searching.
> NOTE: If the input index is optimized (i.e. doesn't contain deletions) then the index produced via IndexWriter.addIndexes(IndexReader[]) will preserve internal document id-s so that they are in sync with the original index. This means that all other auxiliary information not necessary for first-tier processing, such as some stored fields, can also be removed, to be quickly retrieved on-demand from the original index using the same internal document id.
> Threshold values can be specified globally (for terms in all fields) using defaultThreshold parameter, and can be overriden using per-field or per-term values supplied in a thresholds map. Keys in this map are either field names, or terms in field:text format. The precedence of these values is the following: first a per-term threshold is used if present, then per-field threshold if present, and finally the default threshold.
> A command-line tool (PruningTool) is provided for convenience. At this moment it doesn't support all functionality available through API.
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