What is Natural Language Processing?

Natural Language Processing, or NLP for short, analyzes how machines process, interpret and understand human language.

The language of machines and computers is not based on words, but on zeros and ones ordered in a logical way with which only people who master programming languages such as Python, Java or PHP can communicate. Artificial Intelligence, big data or linguistics to break down this communication barrier and helping humans and computers to relate to each otherThe latter can interpret and process different languages.

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Thus, thanks to Natural Language Processing, machines can nowadays read a text, translate a text or a speech into different languages.

However, although there are more than 7,000 languages in the world, for the time being NLP is limited to some of the most widely used languages: English, Chinese, Arabic, SpanishFrench or Portuguese in most cases.

Evolution of Natural Language Processing

Although the term may seem new to us, Natural Language Processing is not a new science. It was born in the 1960s, as a branch of Artificial Intelligence and Linguistics, with the aim of studying the problems derived from the automatic generation and understanding of natural language.

However, in recent years, technological advances as well as the modernization of algorithms have made important contributions to this field.

Natural Language Processing Applications and Uses

Natural Language Processing may be a term that until today was almost unknown to us and has nothing to do with us, is in our daily lives to make our lives easier.. We constantly need it for tasks such as summarizing texts, searching for specific words in a long text, converting a conversation into written text, even maintaining a conversation with assistants such as Alexa, Siri or Google Assistant, which are constantly perfecting their technology to simulate a hyper-realistic human voice that even intones, sings or laughs.

Among the most popular applications of Natural Language Processing are:

• Virtual assistants able to understand human messages and respond automatically to maintain a conversation.
• Machine Translation of texts in any language on the fly. They can even translate a written text from an image.

• Retrieve information by means of keywords. As a result of a question that we ask or specific terms that we give to the machine, it retrieves related information to offer us the most accurate solution. This is the case of Internet search engines.
• Detection of feelings to identify positive, negative or neutral moods or opinions.

Functioning of Natural Language Processing

Although as human beings the language of machines may seem complex to us, our language is also complex for machines. Expressions, different rules of grammar and syntax, colloquial expressions, ironies... represent great challenges that machines must overcome.

To this end, machines need to understand and analyze texts morphological (analysis of words), syntactic (analysis of sentence structure), semantic (interpretation of sentences) and pragmatic (analysis of the context of interpretation).

This is where Natural Language Processing comes into play, which uses different forms of to analyze, understand, and process the text. For example: dividing the text into fragments taking into account capitalization, lower case, synonyms, punctuation marks, etc.; classifying these words according to their typology (articles, verbs, nouns...); analyzing the intentionality of the sentences to detect sarcasm, irony or double meanings; reading long texts to establish associations between words.

GAMCO uses natural language processing in its solutions for business intelligence and law enforcement information. From natural language texts, this technology can achieve, among many other things:

• Quantify the impact of corporate communications in the different communication channels, from the most traditional (press, radio or TV) to the digital ones. This is, for example, Enigma, a reputation analysis tool developed by Gamco.
• Obtain relevant information of certain activities in social networks or on the Internet; in order to track certain activities or people.
• Predict operational or reputational risks to companies.

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