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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 1251–1275 of 4002 papers

TitleStatusHype
ECNU at SemEval-2018 Task 10: Evaluating Simple but Effective Features on Machine Learning Methods for Semantic Difference Detection—0
ECNU: Leveraging Word Embeddings to Boost Performance for Paraphrase in Twitter—0
ECNU: Using Traditional Similarity Measurements and Word Embedding for Semantic Textual Similarity Estimation—0
EDGAR-CORPUS: Billions of Tokens Make The World Go Round—0
Beyond Context: A New Perspective for Word Embeddings—0
EduBERT: Pretrained Deep Language Models for Learning Analytics—0
Effective Context and Fragment Feature Usage for Named Entity Recognition—0
BOUN-ISIK Participation: An Unsupervised Approach for the Named Entity Normalization and Relation Extraction of Bacteria Biotopes—0
Effective Greedy Inference for Graph-based Non-Projective Dependency Parsing—0
Effectiveness of Deep Networks in NLP using BiDAF as an example architecture—0
A Framework for Understanding the Role of Morphology in Universal Dependency Parsing—0
Enabling Open-World Specification Mining via Unsupervised Learning—0
Effect of Text Color on Word Embeddings—0
Effect of Text Processing Steps on Twitter Sentiment Classification using Word Embedding—0
Effects of Creativity and Cluster Tightness on Short Text Clustering Performance—0
Effects of Word Embeddings on Neural Network-based Pitch Accent Detection—0
``A Passage to India'': Pre-trained Word Embeddings for Indian Languages—0
Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering—0
A Cross-lingual Natural Language Processing Framework for Infodemic Management—0
Efficient Contextual Representation Learning Without Softmax Layer—0
Efficient Data Selection for Bilingual Terminology Extraction from Comparable Corpora—0
"A Passage to India": Pre-trained Word Embeddings for Indian Languages—0
Efficient Extraction of Pseudo-Parallel Sentences from Raw Monolingual Data Using Word Embeddings—0
Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space—0
Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks—0
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