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Word Embeddings

Word embedding is the collective name for a set of language modeling and feature learning techniques in natural language processing (NLP) where words or phrases from the vocabulary are mapped to vectors of real numbers.

Techniques for learning word embeddings can include Word2Vec, GloVe, and other neural network-based approaches that train on an NLP task such as language modeling or document classification.

( Image credit: Dynamic Word Embedding for Evolving Semantic Discovery )

Papers

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Showing 3476–3500 of 4002 papers

TitleStatusHype
Convolutional Neural Network for Universal Sentence Embeddings—0
Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings—0
Convolutional Neural Networks for Sentiment Classification on Business Reviews—0
Convolutional Neural Networks for Sentiment Analysis on Weibo Data: A Natural Language Processing Approach—0
Convolutional Sentence Kernel from Word Embeddings for Short Text Categorization—0
Cooperative Self-training of Machine Reading Comprehension—0
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension—0
Coordination Boundary Identification without Labeled Data for Compound Terms Disambiguation—0
CopyBERT: A Unified Approach to Question Generation with Self-Attention—0
Corporate IT-support Help-Desk Process Hybrid-Automation Solution with Machine Learning Approach—0
Corpus specificity in LSA and Word2vec: the role of out-of-domain documents—0
Correcting the Common Discourse Bias in Linear Representation of Sentences using Conceptors—0
Correlation Analysis of Chronic Obstructive Pulmonary Disease (COPD) and its Biomarkers Using the Word Embeddings—0
Count-Based and Predictive Language Models for Exploring DeReKo—0
Country-level Arabic Dialect Identification Using Small Datasets with Integrated Machine Learning Techniques and Deep Learning Models—0
COVID-19 and Arabic Twitter: How can Arab World Governments and Public Health Organizations Learn from Social Media?—0
Creating Causal Embeddings for Question Answering with Minimal Supervision—0
Creation and Evaluation of Datasets for Distributional Semantics Tasks in the Digital Humanities Domain—0
Cross-Document Narrative Alignment of Environmental News: A Position Paper on the Challenge of Using Event Chains to Proxy Narrative Features—0
Cross-Domain Bilingual Lexicon Induction via Pretrained Language Models—0
Cross-language Learning with Adversarial Neural Networks—0
Cross-Language Question Re-Ranking—0
Cross-lingual alignments of ELMo contextual embeddings—0
Cross-Lingual Classification of Topics in Political Texts—0
Cross-Lingual Contextual Word Embeddings Mapping With Multi-Sense Words In Mind—0
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