Natural Language Processing is interaction between computers and human(natural) languages. Specifically, the process of a computer extracting meaningful information from natural language input and producing natural language output. Armed with the above understanding, these computers can perform various analyses on a huge scale, providing professionals with meaningful insights.
Traditionally, communicating with a computer would require giving it very specific, unambiguous, and highly structured instructions, written in exclusive programming languages, like Java or C++
On the other hand, Human language is rarely precise, or plainly spoken. To understand human language is to understand not only the words, but the concepts and how they are linked together to create meaning. Despite language being one of the easiest things for humans to learn, the ambiguity of language is what makes natural language processing a difficult problem for computers to master.
Modern techniques and approaches for NLP are based on what is called machine learning. Machine Learning consists of models and algorithms which are a means to achieve Artificial Intelligence. The above process examines patterns within data to draw conclusions on how natural human languages work. By applying these conclusions, machines can perform tasks including text parsing, speech recognition, parts-of-speech tagging, sentiment analysis and more.
Consider the following tweet on the very popular service offered by Amazon.com called Amazon Prime;
“This amazing service delivers packages to me ASAP”
Using some of the above NLP methods, machines will break down this sentence into its grammatical elements (“amazing” = adjective, “service” = noun, “delivers” = verb, etc.), ASAP is the common acronym for As Soon As Possible. Using this information, Natural Language Processing provides the foundation for further text analytics, like intention detection, event extraction, sentiment analysis and other linguistic analyses.
Though NLP is a relatively recent area of research and application, recent products like Amazon Echo, Google Home etc. have proven that there have been enough successes to date that suggests that NLP will continue to be a major area of focus in research & development in the years to come.
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