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import nltk
from nltk.corpus import stopwords
nltk.download('stopwords')
nltk.download('punkt')
from nltk.tokenize import word_tokenize, sent_tokenize
with open('summarizer_input.txt', 'r', encoding='utf-8') as file:
text = file.read()
stopWords = set(stopwords.words("english"))
words = word_tokenize(text)
freqTable = dict()
for word in words:
word = word.lower()
if word in stopWords:
continue
if word in freqTable:
freqTable[word] += 1
else:
freqTable[word] = 1
sentences = sent_tokenize(text)
sentenceValue = dict()
for sentence in sentences:
for word, freq in freqTable.items():
if word in sentence.lower():
if word in sentence.lower():
if sentence in sentenceValue:
sentenceValue[sentence] += freq
else:
sentenceValue[sentence] = freq
sumValues = 0
for sentence in sentenceValue:
sumValues += sentenceValue[sentence]
average = int(sumValues / len(sentenceValue))
summary = ''
for sentence in sentences:
if (sentence in sentenceValue) and (sentenceValue[sentence] > (1.2 * average)):
summary += " " + sentence
print(summary)