readdata.py 文件源码

def preprocessing(text):
    text = text.decode("utf8")
    # tokenize into words
    tokens = [word for sent in nltk.sent_tokenize(text) for word in nltk.word_tokenize(sent)]

    # remove stopwords
    stop = stopwords.words('english')
    tokens = [token for token in tokens if token not in stop]

    # remove words less than three letters
    tokens = [word for word in tokens if len(word) >= 3]

    # lower capitalization
    tokens = [word.lower() for word in tokens]

    # lemmatize
    lmtzr = WordNetLemmatizer()
    tokens = [lmtzr.lemmatize(word) for word in tokens]
    preprocessed_text= ' '.join(tokens)

    return preprocessed_text