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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 3701–3750 of 4002 papers

TitleStatusHype
ICL-HD at SemEval-2016 Task 10: Improving the Detection of Minimal Semantic Units and their Meanings with an Ontology and Word Embeddings—0
Automatic Triage of Mental Health Forum Posts—0
NUIG-UNLP at SemEval-2016 Task 1: Soft Alignment and Deep Learning for Semantic Textual Similarity—0
UWB at SemEval-2016 Task 7: Novel Method for Automatic Sentiment Intensity Determination—0
Dependency Based Embeddings for Sentence Classification Tasks—0
Amrita\_CEN at SemEval-2016 Task 1: Semantic Relation from Word Embeddings in Higher Dimension—0
VectorWeavers at SemEval-2016 Task 10: From Incremental Meaning to Semantic Unit (phrase by phrase)—0
KeLP at SemEval-2016 Task 3: Learning Semantic Relations between Questions and Answers—0
K-Embeddings: Learning Conceptual Embeddings for Words using Context—0
Learning Cross-lingual Representations with Matrix Factorization—0
Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn't.—0
Diachronic Word Embeddings Reveal Statistical Laws of Semantic ChangeCode0
Query Expansion with Locally-Trained Word Embeddings—0
Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction—0
Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related MessagesCode0
On the Convergent Properties of Word Embedding Methods—0
Problems With Evaluation of Word Embeddings Using Word Similarity Tasks—0
Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vecCode0
Stance and Sentiment in Tweets—0
mwetoolkit+sem: Integrating Word Embeddings in the mwetoolkit for Semantic MWE Processing—0
Example-based Acquisition of Fine-grained Collocation Resources—0
A Comparison of Domain-based Word Polarity Estimation using different Word Embeddings—0
Paraphrasing Out-of-Vocabulary Words with Word Embeddings and Semantic Lexicons for Low Resource Statistical Machine Translation—0
Using Word Embeddings to Translate Named Entities—0
Word Embedding Evaluation and Combination—0
Classifying Out-of-vocabulary Terms in a Domain-Specific Social Media Corpus—0
Neural Scoring Function for MST Parser—0
Distance Metric Learning for Aspect Phrase Grouping—0
Extracting Temporal and Causal Relations between Events—0
Syntactic and semantic classification of verb arguments using dependency-based and rich semantic features—0
Clustering Comparable Corpora of Russian and Ukrainian Academic Texts: Word Embeddings and Semantic Fingerprints—0
From Incremental Meaning to Semantic Unit (phrase by phrase)Code0
Word embeddings and recurrent neural networks based on Long-Short Term Memory nodes in supervised biomedical word sense disambiguation—0
Nonparametric Spherical Topic Modeling with Word EmbeddingsCode0
Cross-lingual Models of Word Embeddings: An Empirical ComparisonCode0
Bilingual Learning of Multi-sense Embeddings with Discrete AutoencodersCode0
Part-of-Speech Relevance Weights for Learning Word Embeddings—0
Enabling Cognitive Intelligence Queries in Relational Databases using Low-dimensional Word Embeddings—0
Multichannel Variable-Size Convolution for Sentence Classification—0
Topic Modeling Using Distributed Word Embeddings—0
Neural Discourse Relation Recognition with Semantic Memory—0
Part-of-Speech Tagging for Historical English—0
Unsupervised word segmentation and lexicon discovery using acoustic word embeddings—0
MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification—0
Character-based Neural Machine Translation—0
Characterizing Diseases from Unstructured Text: A Vocabulary Driven Word2vec ApproachCode0
Easy-First Dependency Parsing with Hierarchical Tree LSTMs—0
Quantifying the vanishing gradient and long distance dependency problem in recursive neural networks and recursive LSTMs—0
Representation of linguistic form and function in recurrent neural networksCode0
Toward Mention Detection Robustness with Recurrent Neural Networks—0
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