By nature, human language is complex. To understand human speech, a technology must also understand the grammatical rules, meaning and context, but also colloquialisms, slang and acronyms used in a language. Natural language processing algorithms support computers by simulating the human ability to understand language.
How does it work? Many NLP algorithms are based on statistics and may be combined with deep learning. This approach is superficial in its analysis of language, however, because it isn’t able to understand the meaning of words. For example, it’s difficult for statistics methods to distinguish the correct meaning for words that have the same form, but different meanings (Bear: verb or noun? Apple: the fruit or the company?). When you consider that the 500 most used words in the English language have an average of 23 different meanings, you can imagine how difficult it is to get it right.
NLP algorithms based on cognitive technologies such as semantic technology put lexicon at the core of their ability to understand language. To disambiguate the meaning of words, this approach identifies all of the structural aspects of the language, consults lexicon databases or semantic networks to reveal all the possible meanings of a word, and makes use of all of the other information present to disambiguate meaning in the proper context. This approach is at the heart of our own Cogito technology.
Today, we can see many examples of Natural Language Processing algorithms at work in everyday life. Machine translation, the automatic translation from one language to another, is a common example. One place that you might find machine translation is on review websites where, for example, restaurant reviews in another language might be automaticallly translated into your language. NLP algorithms are used to provide automatic summarization of the main points in a given text or document. NLP alogirthms are also used to classify text according to predefined categories or classes, and is used to organize information, and in email routing and spam filtering, for example.
Conversational agents such as chatbots also use NLP algorithms to provide a better customer experience. Chatbots provide a human-like conversational experience between the customer and the company on websites, apps or other platforms to help customers get answers to their questions in real time. Virtual assistants like Siri and Alexa and chat applications for online banking and customer service are seeing increasingly wide use. Chatbots and other “smart” applications are using NLP to perform increasingly difficult and complex actions for us such as sharing geo information and retrieving links and images.
Read more about how NLP algorithms will be applied for new applications such as invisible UI, even smarter search and more in this post.