Snowball stemming algorithms, for information retrieval
Stemming algorithms
PyStemmer provides access to efficient algorithms for calculating a
"stemmed" form of a word. This is a form with most of the common
morphological endings removed; hopefully representing a common
linguistic base form. This is most useful in building search
engines and information retrieval software; for example, a search
with stemming enabled should be able to find a document containing
"cycling" given the query "cycles".
PyStemmer provides algorithms for several (mainly european) languages,
by wrapping the libstemmer library from the Snowball project in a
Python module.
It also provides access to the classic Porter stemming algorithm for
english: although this has been superceded by an improved algorithm,
the original algorithm may be of interest to information retrieval
researchers wishing to reproduce results of earlier experiments.
Maintained by: Nikos Giotis
Keywords: PyStemmer,python,stemmer
ChangeLog: PyStemmer
Homepage:
https://github.com/snowballstem/pystemmer/
Download SlackBuild:
PyStemmer.tar.gz
PyStemmer.tar.gz.asc (FAQ)
(the SlackBuild does not include the source)
Individual Files: |
PyStemmer.SlackBuild |
PyStemmer.info |
README |
slack-desc |
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