Global Natural Language Processing Market: Drivers, Restraints, Opportunities, Trends, And Forecasts To 2023

A new report as an Natural Language Processing Market that includes a comprehensive analysis of the global market. Market Overview In the present digitized world, 80% of the data generated is unstructured. Organizations are using natural language processing technology to unravel the meaning of such data to leverage business strategies and opportunities. A myriad of unstructured data is available online in the form of audio content, visual content and social footprints.

Data has now become an asset for organizations. We have arrived into an era of automation of tedious cognitive tasks in businesses. Human beings fundamentally think, communicate and understand in an unstructured manner. Majority of the workflow in business and personal domain are either entirely controlled by humans or involves a human layer that converts the real-world inputs to computer inputs. NLP is gradually becoming ubiquitous in business enterprises and it has a wide array of functions ranging from chatbots and digital assistants such as Google Home, Siri and Alexa to compliance monitoring functions, business intelligence and analytics. Queries, email communication, videos, social media, support requests, customer reviews and so on are sources of useful insights that can be used to generate significant business value.

“The Global Natural Language Processing market is expected to grow at a CAGR of 18.78% during the forecast period 2017–2023.”

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Natural language processing (NLP), also known as computational linguistics is an amalgamation of artificial intelligence, machine learning and linguistics. NLP is one of the most leveraged technologies in artificial intelligence and the growth of the technology is being propelled by the growth of related technologies such as deep learning and cognitive computing. NLP combines artificial intelligence, computer science and computational linguistics to help machines in reading texts by simulating the human ability of understanding languages. The technology offers competitive advantage to businesses in legal, media and digital ad services. Automotive, healthcare, education and the retail sectors are extensively investing in the technology, as NLP is continuously evolving and is capable of interpreting and adapting to a wide variety of human languages. Sentiment analysis is largely used in web and social media monitoring as it gives businesses access to the opinions of end-users about the organization and its services. Useful insights about customer preferences and attitudes can be obtained from the emoticons in social media. The use cases for natural language processing is diverse, covering customer service, autonomous vehicles, healthcare, banking, financial services and insurance (BFSI), manufacturing, retail and consumer goods, media and entertainment, research, education, high tech and electronics.
Global Natural Language Processing Market Key Segments:

On the basis on product:
• Rule-Based
• Statistical
• Hybrid

On the basis of application:
• Information extraction
• Generation Report
• Question answering
• Word processing

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Technological mainstays namely Google, IBM, Microsoft and others are making significant investment in the field of natural language processing. NLP and text analytics have a major role to play in social media sentiment analysis, business intelligence, data governance, cognitive computing and business intelligence. Text analytics is a subset of NLP and is one amongst the two analytics options that NLP offers, alongside speech analytics. NLP helps in establishing relationships in documents, carrying out search, understanding the demarcations of sentences and phrases and determining names and places through semantic technologies. In the context of text analytics, NLP helps in identifying aspects of regulatory compliance, categorization, sentiment analysis and text clustering. NLP solutions are either statistics based, rule based or a hybrid.

Table of Content (TOC):
Chapter 1 Introduction and Overview
Chapter 2 Industry Cost Structure and Economic Impact
Chapter 3 Rising Trends and New Technologies with Major key players
Chapter 4 Global Natural Language Processing Market Analysis, Trends, Growth Factor
Chapter 5 Natural Language Processing Market Application and Business with Potential Analysis
Chapter 6 Global Natural Language Processing Market Segment, Type, Application
Chapter 7 Global Natural Language Processing Market Analysis (by Application, Type, End User)
Chapter 8 Major Key Vendors Analysis of Natural Language Processing Market
Chapter 9 Development Trend of Analysis
Chapter 10 Conclusion

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