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Keyphrase Extraction from Document Using RAKE and TextRank Algorithms

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.9, No. 9)

Publication Date:

Authors : ; ;

Page : 83-93

Keywords : Keyphrase Extraction; Approaches; Natural Language Processing; NLTK- POS Tagging; TF-IDF; RAKE; TextRank; Performance Analysis;

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Abstract

Traditional approaches to extract useful Keyphrase from a sentence rely heavily on human effort. In this paper, to overcome this challenge, Automatic Keyphrase Extraction algorithm has been used to extract a Keyphrase efficiently that reduces the scope for human errors and saves time. The Machine Learning algorithms detect the Keyphrase from a sentence that the user feeds as an input and sets a reminder using the Keyphrase. RAKE and Textrank algorithms help to extract Keyphrase or important terms of a given text document. RAKE and TextRank techniques applied to find and analyze the best possible way of extracting the Keyphrase efficiently. With slight modifications to the code, the algorithms can be implemented to serve different application domain such as message or threat decoding in military purposes and can be extended to use in speech-to-text translation and sentimental analysis of the data.

Last modified: 2020-10-05 20:25:02