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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 1751–1775 of 4002 papers

TitleStatusHype
Exploring Embeddings for Measuring Text Relatedness: Unveiling Sentiments and Relationships in Online Comments—0
Exploring Distributional Representations and Machine Translation for Aspect-based Cross-lingual Sentiment Classification.—0
CNN- and LSTM-based Claim Classification in Online User Comments—0
Exploring Convolutional Neural Networks for Sentiment Analysis of Spanish tweets—0
Exploring Category Structure with Contextual Language Models and Lexical Semantic Networks—0
Exploring Bilingual Word Embeddings for Hiligaynon, a Low-Resource Language—0
How Well Can We Predict Hypernyms from Word Embeddings? A Dataset-Centric Analysis—0
Human-in-the-Loop Refinement of Word Embeddings—0
Cluster Labeling by Word Embeddings and WordNet's Hypernymy—0
Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa - A Large Romanian Sentiment Data Set—0
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning—0
"Hunt Takes Hare": Theming Games Through Game-Word Vector Translation—0
A data-driven strategy to combine word embeddings in information retrieval—0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings—0
Hybridation d'un agent conversationnel avec des plongements lexicaux pour la formation au diagnostic m\'edical (Hybridization of a conversational agent with word embeddings for medical diagnostic training)—0
Hybrid Code Networks using a convolutional neural network as an input layer achieves higher turn accuracy—0
Exploration on Grounded Word Embedding: Matching Words and Images with Image-Enhanced Skip-Gram Model—0
Exploration des relations sémantiques sous-jacentes aux plongements contextuels de mots (Exploring semantic relations underlying contextual word embeddings)—0
Clustering Prominent People and Organizations in Topic-Specific Text Corpora—0
ARHNet - Leveraging Community Interaction for Detection of Religious Hate Speech in Arabic—0
Exploiting Task-Oriented Resources to Learn Word Embeddings for Clinical Abbreviation Expansion—0
Hypothesis Testing based Intrinsic Evaluation of Word Embeddings—0
I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification—0
ICL-HD at SemEval-2016 Task 10: Improving the Detection of Minimal Semantic Units and their Meanings with an Ontology and Word Embeddings—0
Exploiting Position and Contextual Word Embeddings for Keyphrase Extraction from Scientific Papers—0
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