Automatic summarization is the process of reducing a text document with a computer program in order to create a summary that retains the most important points of the original document. With the increasing popularity of Internet and the variety of information obtaining technologies, the amount of quickly growing information has gone beyond our imaginations. Many techniques were presented to help users to find the desired information from large data set quickly and accurately, automatic summarization is an effective approach. Text Summarization methods can be classified into extractive and abstractive summarization. Extractive summaries are created by reusing portions like words, sentences, etc. of the input text exactly. In abstractive summarization, information from the source text is rephrased. Special attention is devoted to automatic evaluation of summarization systems, as future research on summarization is strongly dependent on progress in this area.
Keywords
Knowledge Extraction; Web Document Summarization; Text Summarization; Subject Weight; POS Tagging.
Authors
Dr. N.Preethi
How to Cite this Article
Dr. N.Preethi (2015).
"ANALYSIS ON EXTRACTIVE AUTOMATIC TEXT SUMMARIZATION USING MACHINE LEARNING".
International Journal of Contemporary Research in Computer Science and Technology,
1(3), pp. 87-91.
