Research on Keyword Extraction Algorithm Based on LDA and TF-IDF
In the field of natural language processing,for massive text files,the most crucial task for users to find the documents they are interested in in the shortest possible time is to extract the keywords from each document.Whether targeting a long article or a short article,it is usu-ally possible to directly explore the theme behind the entire article through these keywords.This article introduces the application of LDA topic model and TFIDF algorithm in keyword cx-traction,and compares them.The results show that good results can be achieved in keyword ex-traction.
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