Natural Language Processing (NLP) is defined as the automatic manipulation of “natural language” by software, it is the technology used to allow computers to understand human natural language. The ultimate goal of NLP is to be able to read, decipher, understand, and make sense of human language in a manner that is valuable. But what is “natural language”? It is the way we humans communicate with each other, i.e. speech and text. Clearly, text is everywhere; newspapers, books, text messages, web sites etc, but speech is used even more text.
Working with natural language is hard! This is because language is messy - there are few rules. This sort of unstructured data doesn’t fit well into traditional structures - yet it is exactly this type of data that represents the vast majority of data available in the world today. However, there is currently a big revolution going on in this field and today NLP is booming thanks to advancements in the access to big data and the increase in storage and computational power, which are allowing NLP to achieve meaningful results in areas like healthcare, media, finance and human resources, among others.
Let’s have a look at some of these:
- NLP can enable the recognition and prediction of diseases based on electronic health records. This capability is being explored in health conditions that go from cardiovascular diseases to depression and even schizophrenia. For example, NLP can extract disease conditions, medications and treatment outcomes from patient notes, clinical trial reports and other electronic health records.
- Organisations can use NLP to determine what customers are saying about a their services or products by identifying and extracting information in sources like social media. This analysis can provide a lot of information about customers choices and their decision drivers.
- Mail filters filter and classify your emails with NLP by analysing text in emails and stop spam before it even enters your inbox.
- Alexa, Siri and Cortana are examples of intelligent voice-driven interfaces that use NLP to respond to vocal prompts and do everything from finding a local restaurant, setting an alarm, suggesting the best route to the office or turning on the lights at home.
- NLP can also be used to track news, reports and comments about possible mergers between companies. This information can be then incorporated into trading algorithms.
- NLP is also being used in both the search and selection phases of talent recruitment, identifying the skills of potential hires and also spotting prospects before they become active on the job market.
Natural Language Processing is playing a critical role in supporting machine-human interactions. As further research is being carried in this field, expect to see more breakthroughs that will make machines smarter at recognising and understanding human language.