问题
I'm familiar with word stemming and completion from the tm package in R.
I'm trying to come up with a quick and dirty method for finding all variants of a given word (within some corpus.) For example, I'd like to get "leukocytes" and "leuckocytic" if my input is "leukocyte".
If I had to do it right now, I would probably just go with something like:
library(tm)
library(RWeka)
dictionary <- unique(unlist(lapply(crude, words)))
grep(pattern = LovinsStemmer("company"),
ignore.case = T, x = dictionary, value = T)
I used Lovins because Snowball's Porter doesn't seem to be aggressive enough.
I'm open to suggestions for other stemmers, scripting languages (Python?), or entirely different approaches.
回答1:
This solution requires preprocessing your corpus. But once that is done it is a very quick dictionary lookup.
from collections import defaultdict
from stemming.porter2 import stem
with open('/usr/share/dict/words') as f:
words = f.read().splitlines()
stems = defaultdict(list)
for word in words:
word_stem = stem(word)
stems[word_stem].append(word)
if __name__ == '__main__':
word = 'leukocyte'
word_stem = stem(word)
print(stems[word_stem])
For the /usr/share/dict/words
corpus, this produces the result
['leukocyte', "leukocyte's", 'leukocytes']
It uses the stemming module that can be installed with
pip install stemming
来源:https://stackoverflow.com/questions/31596476/all-possible-wordform-completions-of-a-biomedical-words-stem