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Introduction to Natural Language Processing

Expert.ai Team - 29 May 2020

The market for Natural Language Processing (NLP) is witnessing a continual rise in its valuation as companies in every industry begin to understand its potential. The reason is simple: if computers can understand and interact with people using natural, everyday language, even more intelligent solutions and efficient business processes are possible.

Introduction to Natural Language Processing: Best use cases for NLP

The advancement in artificial Intelligence technologies and the growing interest in interacting with computers using human speech as it is spoken are driving an increasing demand for natural language processing applications. Automation of information-intensive tasks is one of the most popular and effective use cases for NLP. Benefits range from operational and production efficiencies to more effective analysis of data to gain a competitive advantage and new insights.

How Natural Language Processing is Creating Business Value in Companies Today

A key lesson for business can be drawn from the consumer world: the need for simplicity. We’re already using natural language processing and artificial Intelligence technology in our daily lives. They allow us to ask our smartphones where we can find a good restaurant in a new city, and they are probably powering the customer service we use we need to reach out for assistance.

The ability to connect consumers and users to the right information by leveraging natural language interfaces such as Siri or other virtual assistants has its business equivalent: NLP is enabling companies to optimize processes while improving customer satisfaction and increasing user engagement.

Natural language processing transforms the experience for both customers and internal users who can simply ask for what they need and get immediate access to information. By making data accessible, searchable and easily findable, NLP helps streamline access to unstructured information that is trapped in business documents of any type.

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Originally published December 2017, updated May 2020