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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 1176–1200 of 4002 papers

TitleStatusHype
AWE: Asymmetric Word Embedding for Textual Entailment—0
An Empirical Study of Discriminative Sequence Labeling Models for Vietnamese Text Processing—0
Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts—0
Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing - A Tale of Two Parsers Revisited—0
Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing -- A Tale of Two Parsers Revisited—0
A Dynamic Window Neural Network for CCG Supertagging—0
Deep Clustering with Measure Propagation—0
Deep Bidirectional Transformers for Relation Extraction without Supervision—0
Automating Idea Unit Segmentation and Alignment for Assessing Reading Comprehension via Summary Protocol Analysis—0
Deduplication of Scholarly Documents using Locality Sensitive Hashing and Word Embeddings—0
Automatic Word Association Norms (AWAN)—0
An Empirical Analysis of NMT-Derived Interlingual Embeddings and their Use in Parallel Sentence Identification—0
Deconstructing Word Embeddings—0
Deconstructing word embedding algorithms—0
Automatic Triage of Mental Health Forum Posts—0
Deconstructing Complex Search Tasks: a Bayesian Nonparametric Approach for Extracting Sub-tasks—0
Deconstructing and reconstructing word embedding algorithms—0
Automatic Transformation of Clinical Narratives into Structured Format—0
An Embedding Model for Predicting Roll-Call Votes—0
Adversarial Transfer Learning for Punctuation Restoration—0
A Comparison of Domain-based Word Polarity Estimation using different Word Embeddings—0
Decomposing Word Embedding with the Capsule Network—0
Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements—0
Automatic Term Extraction from Newspaper Corpora: Making the Most of Specificity and Common Features—0
Decoding Word Embeddings with Brain-Based Semantic Features—0
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