Named Entity Recognition (NER) is a Natural Language Processing (NLP) technique that consists of identifying and classifying named entities in a text.
Named entities can be any real-world object that has a name of its own, such as people, organisations, locations, dates, times, currencies, among others.
The goal of NER is to identify these entities in a text and classify them into different categories, which can be useful in applications such as sentiment analysis, information extraction, text summarisation, among others.
NER is based on machine learning algorithms that analyse the linguistic features of a text to identify patterns and make decisions about the presence and classification of named entities in it.
You are probably wondering, what is surety insurance and how does it help your company? In today's economic environment, [...]
Read More »Before explaining what artificial intelligence is, we would like to start with a sentence from the book Age of intelligent machines (1992), by Raymond Ku [...]
Read More »Before talking about artificial intelligence in the Fintech market, we would like to mention that the term Fintech is nowadays applied to the technologies that are [...]
Read More »Since 2008, several countries have enacted legislation that recognizes the importance of integrating artificial intelligence (AI) into key areas of life [...]
Read More »
