This is a Rails gem for reducing words to their roots. For example, all the following words to are stemmed to “observ”, which is not a real word in this case: observance observances observancy observant observants observation observe observed observer observers observing
The algorithm used here is based on the Porter stemmer. You can read more about Martin Porter’s stemmer at
tartarus.org/~martin/PorterStemmer/
Martin Porter explains:
The Porter stemming algorithm (or ‘Porter stemmer’) is a process for removing the commoner morphological and inflexional endings from words in English. Its main use is as part of a term normalisation process that is usually done when setting up Information Retrieval systems.
$ sudo gem install stemmify
or
$ gem install stemmify
Note that while the source code is hosted on github, the actual gem is hosted on RubyGem.org.
Let’s say you are building some sort of search tool. You want searches for “observations” and “observer” to all bring up the same items. When you are building you index, you can map all the words to their roots using the stem method.
Here’s an example usage:
require 'stemmify' print("observations".stem) # ==> "observ"
You can use stemmify as a command line tool:
$ stem input_file.txt $ printf "I\nwalked\nin\nthe\nforest\n.\n" | stem
Both the file based input and the input taken from the stdin should be tokenized, i.e. provide one token per line, tokens should be delimeted e.g. by a new line feed.
For tokenization consider using a tokenizer, for instance the tokenizer gem.
This test is based on the sample input and output text from Martin Porter website. It includes 23532 test words and their expected stem results. To run the test, just type
rake test
Dave Thomas from pragprog.com made speed improvements to this code before it was packaged as a gem.
Copyright © 2011 Ray Pereda
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