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.
Keywords: Cosine Similarity, Extractive Summarization, Natural Language Processing (NLP), ROUGE Scores, TF-IDF, TextRank, Text Summarization.
