A Handbook of Computational Linguistics: Artificial Intelligence in Natural Language Processing

Recent Advancements in Text Summarization with Natural Language Processing

Author(s): Asha Rani Mishra* and Payal Garg

Pp: 15-37 (23)

DOI: 10.2174/9789815238488124020004

* (Excluding Mailing and Handling)

Abstract

Computers can now comprehend and interpret human languages thanks to Natural Language Processing (NLP), a subfield of artificial intelligence. NLP is now being used in a variety of fields, including healthcare, banking, marketing, and entertainment. NLP is employed in the healthcare industry for activities like disease surveillance, medical coding, and clinical documentation. NLP may extract relevant data from patient data and clinical notes. Sentiment classification, fraud prevention, and risk management are three areas of finance where NLP is applied. It can identify trends in financial data, spot anomalies that can point to fraud, and examine news stories and social network feeds to learn more about consumer trends and market dynamics. NLP is utilized in marketing for chatbot development, sentiment analysis, and consumer feedback analysis. It can assist in determining the needs and preferences of the consumer, create tailored marketing campaigns, and offer chatbot-based customer care. Speech recognition, language translation, and content suggestion are all uses of NLP in the entertainment industry. In order to suggest movies, TV series, and other material that viewers are likely to love, NLP analyses user behaviour and preferences. It can also translate text between languages and instantly translate audio and video content. It is anticipated that NLP technology will develop further and be used in new fields and use cases. It will soon be a necessary tool for enterprises and organizations in a variety of sectors. In this chapter, we will highlight the overview and adoption of NLP in different applications. Also, this chapter discusses text summarization, an important application of NLP. Different techniques of generating text summaries along with evaluation metrics are the highlights of the chapter.

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