Named Entity Recognition (NER)
Description
A comprehensive look at Named Entity Recognition (NER), a key task in Natural Language Processing. NER involves pinpointing and categorising significant entities within text into predefined groups such as names, locations, and organisations. The documents trace the evolution of NER techniques, from early rule-based systems through statistical machine learning to modern deep learning approaches like LSTMs and Transformers. They also highlight the significance and diverse applications of NER across industries like healthcare, finance, and law, as well as its crucial role in data de-identification for privacy. Finally, the texts address the accuracy, limitations, and future trends of NER technology, including multilingual capabilities and ethical considerations.
United States
