Created
June 5, 2014 20:06
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import re, string, sys, nltk | |
from nltk.stem.wordnet import WordNetLemmatizer | |
from nltk.corpus import wordnet | |
from joblib import Parallel, delayed | |
lmtzr = WordNetLemmatizer() | |
pattern=re.compile(r'[^a-zA-Z ]') | |
def get_wordnet_pos(treebank_tag): | |
if treebank_tag.startswith('J'): | |
return wordnet.ADJ | |
elif treebank_tag.startswith('V'): | |
return wordnet.VERB | |
elif treebank_tag.startswith('R'): | |
return wordnet.ADV | |
else: | |
return wordnet.NOUN | |
def clean(x): | |
x = x.replace('<image>','') | |
x = pattern.sub('',x.lower()) | |
x = x.replace('\r','') | |
x = x.replace('\n','') | |
x = nltk.word_tokenize(x) | |
tag = nltk.pos_tag(x) | |
pos = [] | |
for i in range(len(tag)): | |
pos.append(get_wordnet_pos(tag[i][1])) | |
y = [] | |
for i in range(len(x)): | |
y.append(lmtzr.lemmatize(x[i],pos[i])) | |
x = ' '.join(y) | |
return(x) | |
def final_clean(x,y): | |
a = x.split(',',1) | |
if len(a)==2: | |
c = a[1].replace(',','') | |
b = clean(c) | |
return b | |
f = open("abstracts.txt","rb") | |
f2 = open("abstractsfinal.txt","w") | |
f2.truncate() | |
abstracts = Parallel(n_jobs=30)(delayed(final_clean)(line,f2) for line in f) | |
for i in abstracts: | |
f2.write(str(i) + '\n') |
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