The Five Main Advantages of Natural Language Processing
NLP Lies at the Heart of Man’s Relationship with Machine
Neither humans nor machines are perfect. But natural language processing seeks to break through those imperfections to improve understanding.
Whether it is French, Italian or Fortran-77, learning a new language can be tough. Of course, many would argue that a programming language such as Fortran is easier than a human language as it is based in pure logic. There is none of the nuance that comes with intonation, misspelling or slang to worry about.
When you think about it in that context, you begin to see just how difficult a challenge those at the forefront of natural language processing (NLP) are facing. Put simply, NLP lies at the point where computer science, artificial intelligence and linguistics converge. It seeks to process and “understand” natural language, be it spoken or written, in order to process data, answer questions and interact with humans or, indeed, other technology. As such, NLP is one of the most important aspects of artificial intelligence.
We see examples of NLP every day. Internet search engines, voice control, machine translation, predictive text, chat bots, recommendation systems, the list goes on and on. However, it is in the data analytics sector that NLP can have the most profound impact. Using it, we can accurately predict the outcome of an election without needing to understand the politics, or we can pre-empt a flu epidemic with no medical training.
Keeping people healthier for longer
One of the first places that NLP has been tested is in the medical sector. This is because it can do so much good here in so short a time. If a doctor can look at ten case histories, he can make an assumption with a certain level of confidence. If a system can look at 10,000 case histories in a fraction of the time – the benefits are obvious. The problem is that much medical data is handwritten in long-form text. No check boxes here, the computer needs to read the doctor’s and patient’s notes and understand what they mean despite potential issues with handwriting, terminology, spelling and so on.
From internal chatbots that keep track of vacation records to integrated search that can pull up last month’s financial report, NLP offers businesses an army of virtual assistants just waiting to help. One company that trialled an integrated search tool reported that accounting and customer resource telephone calls were almost ten times shorter with the new system in place.
NLP helps recruiters work their way through CVs, attracting diverse candidates, and ultimately narrowing down a candidate list to the most qualified people being selected for interview.
Keeping a handle on social
Social media is a powerful tool for any business, but it can also become a monster. NLP tools such as sentiment analysis allow businesses to quickly understand the emotion behind social media posts and Tweets, meaning they can rapidly react when necessary. In the past, companies used NLP to discern positive or negative feedback. But today’s tools can take this to the next level, identifying emotions such as anger, fear or sadness.
Better spam detection
Spam filtering is one of the most familiar forms of NLP. As the technology improves, so does the effectiveness of the filters, meaning less junk in our inboxes, and even more importantly, fewer genuine emails being erroneously labelled as spam.