Techniques of Big Data Text Summarization
Anish Mathew Kuriakose1, V.Umadevi2
1Anish Mathew Kuriakose, Ph.D Research Scholar, Department of Computer Science, Jairams Arts and Science College Karur affiliated to Bharathidasan University Tiruchirappalli.
2Dr V. Umadevi, Director, Department of Computer Science,Jairams Arts and Science College Karur affiliated to Bharathidasan University Tiruchirappalli.

Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 9552-9556 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9932118419/2019©BEIESP | DOI: 10.35940/ijrte.D9932.118419

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Abstract: In the web industry 4.0, big data are playing a key role in the organizations of their digital transformation journey. Data has also changed intensely in recent years, in volume, variety and velocity. Its fast development attributed to the extensive digitization of business progressions globally. In simple term, data has turn into the new currency of business and its further quick growth will be key transformation and growth of organizations globally. Vast amount of online information, available in healthcare, social media websites, e-commerce web pages, e-books, legal domain, e-news, etc. has made text processing a vital extent of research. The paper starts with introduction about the evolution of web industry 4.0 and digitalization. Followed by the introduction, the paper discusses about big data and text summarization techniques. Further, it describes the literature of text mining that have taken in the recent years. The main objective of this paper is to discuss about the big data text summarization issues and challenges. The paper starts with general introduction of big data and text mining and text summarization. Further it describes recent advances in big data text summarization, and then delve into extraction and abstraction-based text summarization. Finally, the paper concludes with some future research directions.
Keywords: Web 4.0, Big Data, Text Mining, Text Summarization.
Scope of the Article: Web and Text Mining.