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"Text processing in NLP "

Proud Pigeon answered on June 27, 2023 Popularity 5/10 Helpfulness 2/10

answer "Text processing in NLP "

"Text processing in NLP "

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import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from nltk.stem import PorterStemmer, WordNetLemmatizer
import string

nltk.download('punkt')
nltk.download('stopwords')
nltk.download('wordnet')

def text_preprocessing(text):
    # Tokenization
    tokens = word_tokenize(text)
    
    # Lowercasing
    tokens = [token.lower() for token in tokens]
    
    # Removing punctuation
    tokens = [token for token in tokens if token not in string.punctuation]
    
    # Stop word removal
    stop_words = set(stopwords.words('english'))
    tokens = [token for token in tokens if token not in stop_words]
    
    # Stemming
    stemmer = PorterStemmer()
    tokens = [stemmer.stem(token) for token in tokens]
    
    # Lemmatization
    lemmatizer = WordNetLemmatizer()
    tokens = [lemmatizer.lemmatize(token) for token in tokens]
    
    return tokens

# Example usage
text = "The quick brown fox jumps over the lazy dog."
processed_text = text_preprocessing(text)
print(processed_text)

Popularity 5/10 Helpfulness 2/10 Language python

Source: chat.openai.com

Tags: nlp python

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Contributed on Jun 27 2023

Proud Pigeon

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