https://github.com/wollmers/lingua-stem-cistem
CISTEM Stemmer for German
https://github.com/wollmers/lingua-stem-cistem
cistem-stemmer german stem
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CISTEM Stemmer for German
- Host: GitHub
- URL: https://github.com/wollmers/lingua-stem-cistem
- Owner: wollmers
- License: other
- Created: 2019-08-18T05:39:35.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-08-06T16:15:14.000Z (over 4 years ago)
- Last Synced: 2024-07-30T20:43:00.843Z (9 months ago)
- Topics: cistem-stemmer, german, stem
- Language: Perl
- Size: 88.9 KB
- Stars: 1
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: Changes
- License: LICENSE
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README
# NAME
Lingua::Stem::Cistem - CISTEM Stemmer for German
# SYNOPSIS
use Lingua::Stem::Cistem;
my $stemmed_word = Lingua::Stem::Cistem::stem($word);
my @segments = Lingua::Stem::Cistem::segment($word);
use Lingua::Stem::Cistem qw(:orig);
my $stemmed_word = stem($word);
my @segments = segment($word);
use Lingua::Stem::Cistem qw(:robust);
my $stemmed_word = stem_robust($word);
my @segments = segment_robust($word);
# DESCRIPTION
This is the CISTEM stemmer for German based on the ["OFFICIAL IMPLEMENTATION"](#official-implementation).
Typically stemmers are used in applications like Information Retrieval,
Keyword Extraction or Topic Matching.
It applies the CISTEM stemming algorithm to a word, returning the stem of this word.
Now (2019) CISTEM has the best f-score compared to other stemmers for German on CPAN, while
being one of the fastest.
The methods in this package keep their original logic and API, only the module name
changed from Cistem to Lingua::Stem::Cistem.
Changes in this distribution applied to the ["OFFICIAL IMPLEMENTATION"](#official-implementation):
- packaged for and released on CPAN
- use strict, use warnings
- the method ["stem"](#stem) is 6-9 % faster, ["segment"](#segment) keeps the speed
- undefined parameter word defaults to the empty string ''
- provides two additional methods ["stem\_robust"](#stem_robust) and ["segment\_robust"](#segment_robust) with the same logic as the official ones,
but more robust against low quality input. ["stem\_robust"](#stem_robust) is ~45% and ["segment\_robust"](#segment_robust) ~70 slower.
- Since Version 0.02 the methods ["stem\_robust"](#stem_robust) and ["segment\_robust"](#segment_robust) support a third parameter $keep\_ge\_prefix.
Default is is the previous behavior, i.e. remove the prefix 'ge'.
# OFFICIAL IMPLEMENTATION
It is based on the paper
Leonie Weißweiler, Alexander Fraser (2017).
Developing a Stemmer for German Based on a Comparative Analysis of Publicly Available Stemmers.
In Proceedings of the German Society for Computational Linguistics and Language Technology (GSCL)
which can be read here:
[http://www.cis.lmu.de/~weissweiler/cistem/](http://www.cis.lmu.de/~weissweiler/cistem/)
In the paper, the authors conducted an analysis of publicly available stemmers, developed
two gold standards for German stemming and evaluated the stemmers based on the
two gold standards. They then proposed the stemmer implemented here and show
that it achieves slightly better f-measure than the other stemmers and is
thrice as fast as the Snowball stemmer for German while being about as fast as
most other stemmers.
Source repository [https://github.com/LeonieWeissweiler/CISTEM](https://github.com/LeonieWeissweiler/CISTEM)
# METHODS
Lingua::Stem::Cistem exports no subroutines per default to avoid conflicts with other stemmers.
You can either use the methods without importing the subroutines
use Lingua::Stem::Cistem;
my $stem = Lingua::Stem::Cistem::stem($word);
or import some or all of the methods:
use Lingua::Stem::Cistem qw(stem segment);
my $stem = stem($word);
my @segments = segment($word);
use Lingua::Stem::Cistem qw(:all);
my $stem = stem($word);
Supported:
:all - imports stem segment stem_robust segment_robust
:orig - imports stem segment
:robust - imports stem_robust segment_robust
- stem
stem($word, $case_insensitivity)
This method takes the word to be stemmed and a boolean specifiying if case-insensitive
stemming should be used and returns the stemmed word. If only the word
is passed to the method or the second parameter is 0, normal case-sensitive stemming is used,
if the second parameter is 1, case-insensitive stemming is used.
Case sensitivity improves performance only if words in the text may be incorrectly upper case.
For all-lowercase and correctly cased text, best performance is achieved by
using the case-sensitive version.
- stem\_robust
stem_robust($word, $case_insensitivity, $keep_ge_prefix)
This method works like ["stem"](#stem) with the following differences for robustness:
- German Umlauts in decomposed normalization form (NFD) work like composed (NFC) ones.
- Other characters plus combining characters are treated as graphemes, i.e. with length 1
instead of 2 or more, which has an influence on the resulting stem.
- The characters $, %, & keep their value, i.e. they roundtrip.
- If parameter $keep\_ge\_prefix is set, prefix 'ge' is kept in the stem. Be careful
if this really improves the results. Mostly removing 'ge' performs better.
This should not be necessary, if the input is carefully normalized, tokenized, and filtered.
- segment
segment($word, $case_insensitivity)
This method works very similarly to stem. The only difference is that in
addition to returning the stem, it also returns the rest that was removed at
the end. To be able to return the stem unchanged so the stem and the rest
can be concatenated to form the original word, all subsitutions that altered
the stem in any other way than by removing letters at the end were left out.
my ($stem, $suffix) = segment($word);
- segment\_robust
segment_robust($word, $case_insensitivity, $keep_ge_prefix)
This method works exactly like ["stem\_robust"](#stem_robust) and returns a list of prefix, stem and suffix:
my ($prefix, $stem, $suffix) = segment_robust($word);
# SPEED COMPARISON
Tests were run using the file goldstandard1.txt (317441 words, 3.76 MB), which can be
found here:
[https://github.com/LeonieWeissweiler/CISTEM/blob/master/gold\_standards/goldstandard1.txt](https://github.com/LeonieWeissweiler/CISTEM/blob/master/gold_standards/goldstandard1.txt)
The test iterates over the words in the file. Times measured include the overhead of startup and iteration.
Platform (only one thread used)
Intel Core i7-4770HQ Processor
4 Cores, 8 Threads
2.20 - 3.40 GHz
6 MB Cache
16GB DDR3 RAM
MacOS Mojave Version 10.14.4
Perl 5.20.1
+-------------------------------------------------------------+
| source: goldstandard1.txt | words: 317441 |
+-------------------------------------------------------------+
| method | version | duration | factor | words/sec |
|-------------------------------------------------------------|
| stem | official | 2.862s | 1.00 | 110916 |
| stem | this v0.01 | 2.678s | 0.94 | 118536 |
| stem_robust | this v0.01 | 4.111s | 1.44 | 77217 |
| | | | | |
| segment | official | 2.594s | 1.00 | 122375 |
| segment | this v0.01 | 2.642s | 1.02 | 120151 |
| segment_robust | this v0.01 | 4.368s | 1.68 | 72674 |
+-------------------------------------------------------------+
# SOURCE REPOSITORY
[http://github.com/wollmers/Lingua-Stem-Cistem](http://github.com/wollmers/Lingua-Stem-Cistem)
# AUTHOR
Helmut Wollmersdorfer
# COPYRIGHT
Copyright 2019-2020 Helmut Wollmersdorfer
Copyright 2017 Leonie Weißweiler (original version)
# LICENSE
This library is free software; you can redistribute it and/or modify
it under the same terms as Perl itself.
# SEE ALSO
[Lingua::Stem::Snowball](https://metacpan.org/pod/Lingua%3A%3AStem%3A%3ASnowball), [Lingua::Stem::UniNE](https://metacpan.org/pod/Lingua%3A%3AStem%3A%3AUniNE), [Lingua::Stem](https://metacpan.org/pod/Lingua%3A%3AStem), [Lingua::Stem::Patch](https://metacpan.org/pod/Lingua%3A%3AStem%3A%3APatch)