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
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Article
• 語言: English
• 出版: 2020
• 主題: Engineering::Electrical and electronic engineering; Word Embeddings; Extreme Learning Machine (ELM)
• 在線閱讀: https://hdl.handle.net/10356/141680

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...