Abstract
Text Summarization is the process of generating a concise and meaningful summary of a text. To better help identify relevant information and consume relevant information faster, automatic text summarizing methods are needed to address the growing amount of text data available online. Text Summarization techniques are classified into abstractive and extractive summarization. The extractive summarization technique focuses on important information like sentences or phrases which are extracted from a given text file or original document and stack them together to create a summary. In this study, we review and compare the performance of three extraction-based summarization techniques which are Conceptual method, Text Rank and Sentence Scoring. Furthermore, we evaluate the quality of summarization by comparing individual methods on unsummarized text with their corresponding human made gold standard summaries.
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