Natural Language Processing

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It wasn’t long after someone came up with the idea of a robot that people wanted it to understand human speech and text. It was a dream that could only be found in the pages of science fiction books and short stories, or observed in movies. Known as Natural Language Processing (NLP), the concept of a computer understanding human speech and text is now here.

It is not an easy task to achieve. First, there is the problem of human’s speaking in a concise manner so that a machine can understand. Second, the problem of words that sound the same, but have different meanings like weigh and way, weight and wait, etc.

How Natural Language Processing Works

Processing the spoken or written word relies heavily on Big Data, large amounts of structured, semi-structured, and unstructured data that can be mined for information. Computers can quickly go through the data, analyze it, and find patterns or trends. Initially, NLP relied on basic rules where machines using algorithms were told what words and phrases to look for in text and then taught specific responses when the phrases appeared. It has evolved into deep learning, a flexible, more instinctive method in which algorithms are used to teach a machine to identify a speaker’s intent from a series of examples.

In the evolution of NLP, algorithms have been historically bad at interpreting. However, now with improvements in deep learning and AI, algorithms can now successfully interpret.

If you own an Amazon Echo or a Google Home, then you are interacting with artificial intelligence and NLP. Moreover, it is already being used in all sorts of business applications including manufacturing, business analytics, customer relations, human resources, and healthcare.

NLP, AI, And Businesses

In the coming years, Natural Language Processing and Artificial Intelligence will influence five areas of healthcare.

  • Clinical Data and Administrative Assistants
  • Data Mining and Extraction
  • Market Analysis
  • Real-Time Translation Services

In customer service, the use of NLP can help determine customer attitudes for future sales. There will be no need for customer surveys. Instead, mining systems will offer deeper insights about a customer’s feelings. Chatbots will allow human customer service personnel to concentrate on other types of calls.

NLP will help human resource departments to recruit job seekers, will make it easier to sort through resumes, attract more specific candidates, and hire more qualified workers. NLP in spam detection will keep unwanted emails out of an executive’s inbox. It can also be used to “read” tweets and determine whether they are good or bad for a company so that customer concerns can be addressed.

NLP And Social Good

NLP and AI can help prevent school shootings. For example, Columbia University researchers have processed 2 million tweets posted by 9,000 at-risk youth to determine how language changes as a teen gets closer and closer to committing a violent act.

There are so many uses for NLP now and, no doubt, as the technology expands, more can be achieved.

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