Is it possible to to change words like running, helping, cooks, finds and happily into run, help, cook, find and happy using nltk?
There are some stemming algorithms implemented in nltk. It looks like Lancaster stemming algorithm will work for you.
>>> from nltk.stem.lancaster import LancasterStemmer
>>> st = LancasterStemmer()
>>> st.stem('happily')
'happy'
>>> st.stem('cooks')
'cook'
>>> st.stem('helping')
'help'
>>> st.stem('running')
'run'
>>> st.stem('finds')
'find'
>>> from nltk.stem import WordNetLemmatizer
>>> wnl = WordNetLemmatizer()
>>> ls = ['running', 'helping', 'cooks', 'finds']
>>> [wnl.lemmatize(i) for i in ls]
['running', 'helping', u'cook', u'find']
>>> ls = [('running', 'v'), ('helping', 'v'), ('cooks', 'v'), ('finds','v')]
>>> [wnl.lemmatize(word, pos) for word, pos in ls]
[u'run', u'help', u'cook', u'find']
>>> ls = [('running', 'n'), ('helping', 'n'), ('cooks', 'n'), ('finds','n')]
>>> [wnl.lemmatize(word, pos) for word, pos in ls]
['running', 'helping', u'cook', u'find']
See Porter Stemming of fried
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