What are some applications of word embeddings in environmental research? How can word embeddings be used in cybersecurity?

Apr 11, 2016 ... Word embeddings popularized by word2vec are pervasive in current NLP applications. The history of word embeddings, however, goes back a lot ... This book provides a high level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector. Nov 4, 2022 ... Word embeddings aim to capture the semantic meaning of words in a sequence of text. It assigns similar numerical representations to words that have similar ... Nov 27, 2021 ... We also discuss NLP basics, especially word embedding models, and give a short review of how occupations have been analyzed using NLP methods. How should we represent the meaning of a word? In the n-gram models of Chapter 3, and in classical NLP applications, our only representation of a word is as a ... vectors (embeddings), we significantly outperform a classical model. Key words: word embedding, natural language processing, PCA, artificial neural networks,. Highlights. •. Radiopaedia can be used as a domain-specific corpus in radiology NLP tasks. •. Domain specific embeddings offer comparable performance on analogy ... ... word embeddings to NLP tasks. Bender et al. (2021) outline how the very ... Mapping words (or other tokens) to an embedding in a special vector space is a ... Mar 29, 2021 ... Recent studies have revealed a security threat to natural language processing (NLP) models, called the Backdoor Attack. Victim models can ... Aug 28, 2023 ... In the realm of Natural Language Processing (NLP) and AI, understanding text similarity is a critical component for various applications, ...