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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 1326–1350 of 4002 papers

TitleStatusHype
En-Ar Bilingual Word Embeddings without Word Alignment: Factors Effects—0
Encoders Help You Disambiguate Word Senses in Neural Machine Translation—0
Can Existing Methods Debias Languages Other than English? First Attempt to Analyze and Mitigate Japanese Word Embeddings—0
Encoding Prior Knowledge with Eigenword Embeddings—0
Encoding Sentiment Information into Word Vectors for Sentiment Analysis—0
Aligning Open IE Relations and KB Relations using a Siamese Network Based on Word Embedding—0
End-to-End Entity Linking and Disambiguation leveraging Word and Knowledge Graph Embeddings—0
Active Discriminative Text Representation Learning—0
Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications—0
Captioning Images with Novel Objects via Online Vocabulary Expansion—0
ENGLAWI: From Human- to Machine-Readable Wiktionary—0
English-Malay Cross-Lingual Embedding Alignment using Bilingual Lexicon Augmentation—0
English-Malay Word Embeddings Alignment for Cross-lingual Emotion Classification with Hierarchical Attention Network—0
English Resource Semantics—0
English WordNet Random Walk Pseudo-Corpora—0
A Preliminary Study on a Conceptual Game Feature Generation and Recommendation System—0
Enhanced Word Representations for Bridging Anaphora Resolution—0
Evaluating Biomedical BERT Models for Vocabulary Alignment at Scale in the UMLS Metathesaurus—0
Case Studies on using Natural Language Processing Techniques in Customer Relationship Management Software—0
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques—0
Enhancing Clinical Concept Extraction with Contextual Embeddings—0
Casteism in India, but Not Racism - a Study of Bias in Word Embeddings of Indian Languages—0
Enhancing General Sentiment Lexicons for Domain-Specific Use—0
Evaluating Feature Extraction Methods for Knowledge-based Biomedical Word Sense Disambiguation—0
Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to Modeling—0
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