Treffer: Summarized application using natural language processing method.

Automatic summarization of articles in this big data era is essential to help extract or abstract the most critical points out in a short period. A previous comparative study of extractive algorithms shows that Sukma_Textrank gives the best F score and lowest mean among SMMRY and TextSummarizer for 30 BBC articles. Thus, in this study, Sukma_Textrank was employed to build an automatic summarized application using the natural language processing method, python, HTML and PHP codes. Three linguistics articles were summarized using the built App and compared with SMMRY and TextSummarizer using ROUGE 2.0. Again, it shows that the developed App using Sukma_Textrank outperformed the other two extractive algorithms. [ABSTRACT FROM AUTHOR]

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