What about NLP today?

Cath Sandoval
Copywritter

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Nowadays we all want machines to talk, and the only way a computer can talk is through Natural Language Processing (NLP). 

A clear example of this is Alexa, an Amazon product. A query is passed to it by voice, and it can respond by the same means, i.e. voice. It can also be used to ask anything, search for anything, play songs or even book a cab.

However, Alexa is not just one example, and these talking machines that are popularly known as chatbot can even manage complicated interactions and optimized business related processes using only NLP. In the past, chatbots were used only for customer interaction with limited conversational capabilities because they were usually rule-based, but after the emergence of Natural Language Processing and its integration with machine learning and Deep Learning, now the chatbot can handle many different areas, such as Human Resources, healthcare among others.

Now let’s take a brief look at other PLN use cases. Here are a few that xenonstack shares in his article:

  • NLP in healthcare: in this case we will be able to make a prediction of different diseases by using pattern recognition methods and the patient’s speech and electronic health record. An example of this is Amazon Comprehend Medical.
  • Sentiment Analysis using NLP: Sentiment analysis is very relevant, since it has the ability to provide a great amount of knowledge about the customer’s behavior and choices, which can be considered as an important decision factor.
  • Cognitive Analytics and NLP: Using NLP, conversational frameworks have the ability to take commands through voice or text. By using cognitive analytics, it is possible to automate different technical processes, such as the generation of a technical ticket related to a technical problem and also its handling in an automated or semi-automated way.

The collaboration of these techniques results in an automated process of handling technical problems within a company. It can also provide the solution of some technical issues to the customer in an automated way.

  • Spam detection: Google and Yahoo are known to use NLP to classify and filter emails suspected of being spam. This process is known as Spam Detection and Filtering. This results in an automated process that can classify email as spam and stop it from entering the Inbox.
  • NLP in Recruitment: NLP is also used in both search and screening phases of job recruitment, even, chatbot can also be used to handle the job related query at the initial level. This also includes identifying the skills required for a specific job and handling entry level tests and exams.
  • Conversational Framework: NLP and related devices are gaining a lot of popularity these days. Alexa, is one of them, also Apple’s Siri and Google’s Ok Google, which are examples of the same type of technology use cases.

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