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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 3576–3600 of 4002 papers

TitleStatusHype
Character-based Neural Machine Translation—0
Subsumption Preservation as a Comparative Measure for Evaluating Sense-Directed Embeddings—0
Modeling the Non-Substitutability of Multiword Expressions with Distributional Semantics and a Log-Linear Model—0
Modelling the Combination of Generic and Target Domain Embeddings in a Convolutional Neural Network for Sentence Classification—0
Unsupervised Text Segmentation Using Semantic Relatedness GraphsCode0
Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time—0
bot.zen @ EmpiriST 2015 - A minimally-deep learning PoS-tagger (trained for German CMC and Web data)—0
Morphological Smoothing and Extrapolation of Word Embeddings—0
Using Embedding Masks for Word Categorization—0
Using Word Embeddings for Improving Statistical Machine Translation of Phrasal Verbs—0
Bilingual Embeddings and Word Alignments for Translation Quality Estimation—0
Bidirectional Recurrent Convolutional Neural Network for Relation Classification—0
A Word Embedding Approach to Identifying Verb-Noun Idiomatic Combinations—0
Multi-Modal Representations for Improved Bilingual Lexicon Learning—0
Sparsifying Word Representations for Deep Unordered Sentence Modeling—0
Phrase Representations for Multiword Expressions—0
Spanish NER with Word Representations and Conditional Random Fields—0
Roleo: Visualising Thematic Fit Spaces on the Web—0
On the Role of Seed Lexicons in Learning Bilingual Word Embeddings—0
Language Transfer Learning for Supervised Lexical Substitution—0
When Hyperparameters Help: Beneficial Parameter Combinations in Distributional Semantic Models—0
Singleton Detection using Word Embeddings and Neural Networks—0
Parameterized context windows in Random Indexing—0
SimpleNets: Quality Estimation with Resource-Light Neural Networks—0
An Improved Crowdsourcing Based Evaluation Technique for Word Embedding Methods—0
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