Summary

Importre
Fromnltk.tokenizeimportsent_tokenize
Fromsklearn.feature_extraction.textimportTfidfVectorizer
Fromsklearn.metrics.pairwiseimportcosine_similarity
#Texttosummarize
Text=“Helloall,WelcometoPythonProgrammingAcademy.PythonProgrammingAcademyis
aniceplatformtolearnnewprogrammingskills.ItisdifficulttogetenrolledinthisAcademy.”
#Preprocessthetexttoremovespecialcharactersanddigits
Preprocessed_text=re.sub(r’[^a-zA-Z\s]’,‘’,text)
#Tokenizethepreprocessedtextintosentences
Sentences=sent_tokenize(preprocessed_text)
#CalculatetheimportancescoreofeachsentenceusingTF-IDF
Vectorizer=TfidfVectorizer()
Tfidf_matrix=vectorizer.fit_transform(sentences)
Similarity_matrix=cosine_similarity(tfidf_matrix)
#SelecttopNsentencesbasedontheirimportancescore
N=2
Top_sentences=sorted(range(len(similarity_matrix[-1])),key=lambdai:similarity_matrix[-1][i])[-
N:]
#Concatenatethetopsentencestoformthesummary
Summary=‘’
Foriintop_sentences:
Summary+=sentences[i]+‘‘
Print(summary)