It was so long after someone came up with the idea of a robot, where people wanted to understand human speech and text. It was a dream that can only be found in the pages of science fiction books and short stories, or that can be seen in movies. Known as "natural language processing" (NLP), the concept of a computer that understands human speech and text now exists.
It is not an easy task to accomplish. First, there is a problem that man speaks succinctly so that the machine can understand it. Second, the problem of words seems similar, but has different meanings such as weight, method, weight, hold, etc.
How natural language processing works
Speech or written word processing is highly dependent on big data, and large amounts of structured, semi-structured, and unstructured data that can be extracted to obtain information. Computers can quickly go through the data, analyze them, and find patterns or trends. Initially, NLP depended on the basic rules where machines that used algorithms were told with words and phrases to search for in the text, and then taught specific responses when sentences appeared. It has evolved into a deep learning, flexible and more instinctive way in which algorithms are used to teach a machine to determine the intention of a speaker from a series of examples.
In the development of NLP, algorithms have historically been poorly interpreted. However, now with improvements in deep learning and AI, algorithms can now be successfully translated.
If you own Amazon Echo or Google Home, you are interacting with artificial intelligence and NLP. Moreover, it is already used in all types of business applications including manufacturing, business analytics, customer relations, human resources and healthcare.
NLP, AI, and Corporate
In the coming years, natural language processing and artificial intelligence will affect five areas of healthcare.
- Clinical data and administrative assistants
- Data extraction and extraction
- Market analysis
- Interpretation services
In customer service, the use of NLP can help define customer attitudes for future sales. There will be no need for customer surveys. Instead, mining systems will provide deeper insights into customer feelings. Chatbots will allow human customer service staff to focus on other types of calls.
NLP will assist HR departments to recruit job seekers, and it will facilitate the screening process by CVs, attract more recruited candidates, and recruit more qualified workers. NLP Detecting Spam will keep unwanted emails out of the executive mailbox. It can also be used to "read" Tweets and determine whether they are good or bad for the 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 handled two million tweets posted by 9,000 young men at risk to determine how language changes when a teenager is closer and closer to buying violent work.
There are many uses in NLP now, and there is no doubt that as technology expands, more can be done.