What is Natural Language Processing?

Natural Language Processing (NLP) is a field of artificial intelligence which aims to improve the relationship between human language and computer language. Its origins date back to the period directly following the end of the Second World War, during which time the prospect of accomplishing some means of mechanical language translation was placed at a premium.

The field of NLP persisted into its expansive modern form due to the emergence of computers as everyday tools and the studiously recorded dissonance between human and computer language which came along with that. The challenge is that we humans chiefly learn to interpret our native languages/dialects (English, Spanish, French, Mandarin, etc.) in an unstructured way through years of socialization. We may initially learn the rules of our language through academia, but as we grow, we rely predominantly on our surrounding cultures to assign meanings to specific words and phrases, which then slowly change shape over time. Since computers conversely rely on rigidly structured, quantifiable data to communicate with one another, they cannot natively interpret asynchronous, evolving human languages on their own, and must be rigorously trained to do so as a result.

Why is NLP Important, and How is it achieved?

Natural Language Processing combines a variety of scientific fields – including computer science, linguistics, mathematics, and psychology – with the goal of structuring linguistic data in such a way that computers can successfully and efficiently predict the meaning of human sentences (in any given language; NLP is highly language-specific). Successfully predicting the meaning of written language allows computers to both draw insights from and reproduce human language on their own, increasing the range of useful services computer applications can provide to human users. Given that, in the modern digital era, an increasingly high volume of human interactions occurs online in an automated fashion, NLP capabilities have quickly transformed into a necessity rather than a luxury.

The high-level NLP training process starts with tokenizing vast quantities of reference text into individual words and tagging each token with the part-of-speech category it belongs to (i.e., verb, noun, adjective, etc.). Once language has been tokenized and tagged, parsing algorithms can be applied to establish relationships between different tokens, enabling computers to discern how words tend to occur (in what order) in any given language’s phrases or clauses. These basic building blocks make it possible for applications to perform several rudimentary NLP services – many of which we have benefited from for a long time (like spellcheck, for example).

From these building blocks, various complex subfields of NLP branch out to train computers with specific contextual understandings which are pivotal to a well-rounded understanding of any human language. Some subfields include Sentiment Analysis (identifying the meaning of text as positive, negative, or neutral), Subjectivity/Objectivity Analysis (identifying the bias inherent in a text string), Semantic Similarity Comparison (identifying the degree to which two sentences with different words mean the same thing semantically), and more. Techniques such as these effectively empower our applications to draw meaningful insights from text on their own, rather than simply predict and reproduce words in the correct grammatical order.

Cloudmersive NLP APIs

Creating any NLP service from scratch is a significant challenge given the vast quantities of data involved (bringing overhead storage cost into play) and the hands-on training required to bestow meaning upon that data. As a result, it is highly efficient and advantageous to incorporate NLP services into any application through external, RESTful API calls. This method loosely couples a business’ text data with a powerful, pre-existing reference dataset & codebase without the need to update or maintain those systems whatsoever.

Cloudmersive NLP APIs are low-code solutions designed to easily integrate and scale with your business’ needs. There are dozens of useful NLP services available through the Cloudmersive NLP API endpoint, including NLP Analytics, Language Translation, Spellcheck, and more.

For more information on our NLP APIs, please do not hesitate to contact a member of our sales or support teams.