Comparative Study on Keyword Extraction Algorithms for Single Extractive Document

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Abstract

The Automatic Text Summarization is most discussed area in Text Mining; there are various techniques available in text mining for text summarization. The two type of summarization are the extractive and abstractive text summarization. The main aim of text summarization is to obtain the concise meaningful text from the original text document. Keywords plays an important role in building a summarization text, there are several keyword extraction algorithms were proposed. In this paper, we implemented most popular keyword extraction algorithms the TF-IDF(a baseline algorithm), TextRank and RAKE algorithm. These keywords extraction algorithms were tested their effectiveness in finding important keywords from single document; the retrieved keywords are compared with the manually selected keywords. The comparison is performed to check the performance of each implemented algorithms with each other and with manually selected keywords.

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