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articles = data["Article"].tolist()
uni_tfidf = text.TfidfVectorizer(input=articles, stop_words="english")
uni_matrix = uni_tfidf.fit_transform(articles)
uni_sim = cosine_similarity(uni_matrix)
def recommend_articles(x):
return ", ".join(data["Title"].loc[x.argsort()[-5:-1]])
data["Recommended Articles"] = [recommend_articles(x) for x in uni_sim]
data.head()
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