Question

In: Computer Science

in python: (can use ntlk) Given the following documents: • Can we go to Disney??!!!!!! Let's...

in python: (can use ntlk)

Given the following documents:

• Can we go to Disney??!!!!!! Let's go on a plane!

• The New England Patriots won the Super Bowl..

• I HATE going to school so early

• When will I be considered an adult?

• I want to go to A&M, Baylor, or the University of Texas.

Conduct punctuation removal, stop word removal, casefolding, lemmatization, stemming on the documents.

Solutions

Expert Solution

#!/usr/bin/env python
# coding: utf-8

# In[4]:


from nltk.tokenize import word_tokenize
text = "Can we go to Disney Land???!!! Let's go on a plane!"
tokens = word_tokenize(text)
tokens = [x.lower() for x in tokens]
tokens


# In[5]:


import re
regex = re.compile(r'[\W\d]')
post_punctuation = []
for word in tokens:
    word = re.sub(regex,'',word)
    if len(word)>0:
        post_punctuation.append(word)
post_punctuation


# In[6]:


from nltk.corpus import stopwords
no_stop_words = []
for word in post_punctuation:
    if word not in stopwords.words('english'):
        no_stop_words.append(word)
no_stop_words


# In[7]:


from nltk.stem import WordNetLemmatizer
word_lem = WordNetLemmatizer()
for word in no_stop_words:
    word = word_lem.lemmatize(word)
no_stop_words


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