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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 3901–3925 of 4002 papers

TitleStatusHype
Reading Between the Lines: Overcoming Data Sparsity for Accurate Classification of Lexical Relationships—0
CroVeWA: Crosslingual Vector-Based Writing Assistance—0
MITRE: Seven Systems for Semantic Similarity in Tweets—0
ECNU: Using Traditional Similarity Measurements and Word Embedding for Semantic Textual Similarity Estimation—0
Associating Neural Word Embeddings With Deep Image Representations Using Fisher Vectors—0
Improved Relation Extraction with Feature-Rich Compositional Embedding ModelsCode0
Document-Level Machine Translation with Word Vector Models—0
Adapting word2vec to Named Entity Recognition—0
Random Walks and Neural Network Language Models on Knowledge Bases—0
Unsupervised Morphology Induction Using Word Embeddings—0
Simple task-specific bilingual word embeddings—0
Combining Word Embeddings and Feature Embeddings for Fine-grained Relation ExtractionCode0
A Word Embedding Approach to Predicting the Compositionality of Multiword Expressions—0
Ontologically Grounded Multi-sense Representation Learning for Semantic Vector Space Models—0
Unsupervised Most Frequent Sense Detection using Word Embeddings—0
Deep Multilingual Correlation for Improved Word Embeddings—0
Word Embedding-based Antonym Detection using Thesauri and Distributional Information—0
Morphological Word-Embeddings—0
Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space—0
Learning Dictionaries for Named Entity Recognition using Minimal Supervision—0
Classifying Relations by Ranking with Convolutional Neural NetworksCode0
Big Data Small Data, In Domain Out-of Domain, Known Word Unknown Word: The Impact of Word Representation on Sequence Labelling Tasks—0
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding—0
Automatic Noun Compound Interpretation using Deep Neural Networks and Word Embeddings—0
Unsupervised POS Induction with Word Embeddings—0
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