Named Entity Recognition (NER)

Concept and definition

Named Entity Recognition (NER)

What is Named Entity Recognition (NER)?

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.

« Back to glossary

Do you want to get in touch?

CDRs contain data that a telecommunications company collects about phone calls, such as time and length of call. This data can be used in analytical applications.
Fill the form
Share:
The best fraud detection software

Fraud detection software is an important tool for protecting companies and individuals from fraudulent activity and minimizing the risk of fraud.

Read More »
Best Deep Learning applications and software

Deep learning translates as deep learning and is a type of artificial intelligence (AI) that is encompassed within machine learning.

Read More »
How does semantic technology work?�

To know how semantic technology works, the first thing you need to know is that it is responsible for helping artificial intelligence systems [...]

Read More »
What is an ERP? Functions and why a company should have it

ERP stands for Enterprise Resource Planning and is a computerized planning and business management system capable of integrating the information [...]

Read More »
See more entries
© Gamco 2021, All Rights Reserved - Legal notice - Privacy - Cookies