Generating word embeddings from an extreme learning machine for sentiment analysis and sequence labeling tasks

• Main Authors: Lauren, Paula, Qu, Guangzhi, Yang, Jucheng, Watta, Paul, Huang, Guang-Bin, Lendasse, Amaury
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2020
• Subjects: Engineering::Electrical and electronic engineering; Word Embeddings; Extreme Learning Machine (ELM)
• Online Access: https://hdl.handle.net/10356/141680
• Institution: Nanyang Technological University

Word Embeddings are low-dimensional distributed representations that encompass a set of language modeling and feature learning techniques from Natural Language Processing (NLP). Words or phrases from the vocabulary are mapped to vectors of real numbers in a low-dimensional space. In previous work, w...