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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 2551–2600 of 4002 papers

TitleStatusHype
A Chinese Writing Correction System for Learning Chinese as a Foreign Language—0
Convolutional Neural Network for Universal Sentence Embeddings—0
Task-oriented Word Embedding for Text ClassificationCode0
A Review on Deep Learning Techniques Applied to Answer Selection—0
Simple Algorithms For Sentiment Analysis On Sentiment Rich, Data Poor Domains.—0
Attending Sentences to detect Satirical Fake News—0
Why does PairDiff work? - A Mathematical Analysis of Bilinear Relational Compositional Operators for Analogy Detection—0
Authorless Topic Models: Biasing Models Away from Known StructureCode0
Contextual String Embeddings for Sequence LabelingCode0
Learning Emotion-enriched Word Representations—0
RuSentiment: An Enriched Sentiment Analysis Dataset for Social Media in Russian—0
Joint Learning from Labeled and Unlabeled Data for Information Retrieval—0
From Text to Lexicon: Bridging the Gap between Word Embeddings and Lexical ResourcesCode0
Relation Induction in Word Embeddings Revisited—0
A New Approach to Animacy Detection—0
Transition-based Neural RST Parsing with Implicit Syntax FeaturesCode0
Recognizing Humour using Word Associations and Humour Anchor Extraction—0
Learning Word Meta-Embeddings by AutoencodingCode0
Summarization Evaluation in the Absence of Human Model Summaries Using the Compositionality of Word Embeddings—0
Enriching Word Embeddings with Domain Knowledge for Readability Assessment—0
Enhancing General Sentiment Lexicons for Domain-Specific Use—0
Encoding Sentiment Information into Word Vectors for Sentiment Analysis—0
Cross-Document Narrative Alignment of Environmental News: A Position Paper on the Challenge of Using Event Chains to Proxy Narrative Features—0
Identifying Aggression and Toxicity in Comments using Capsule Network—0
Learning Diachronic Analogies to Analyze Concept ChangeCode0
Exploring word embeddings and phonological similarity for the unsupervised correction of language learner errors—0
Transferred Embeddings for Igbo Similarity, Analogy, and Diacritic Restoration Tasks—0
Aggression Identification and Multi Lingual Word Embeddings—0
Veyn at PARSEME Shared Task 2018: Recurrent Neural Networks for VMWE IdentificationCode0
Automatically Linking Lexical Resources with Word Sense Embedding Models—0
Mumpitz at PARSEME Shared Task 2018: A Bidirectional LSTM for the Identification of Verbal Multiword Expressions—0
Textual Aggression Detection through Deep Learning—0
TRAC-1 Shared Task on Aggression Identification: IIT(ISM)@COLING'18—0
Aggressive Language Identification Using Word Embeddings and Sentiment FeaturesCode0
Word-Embedding based Content Features for Automated Oral Proficiency Scoring—0
Sub-label dependencies for Neural Morphological Tagging -- The Joint Submission of University of Colorado and University of Helsinki for VarDial 2018—0
Gender Bias in Neural Natural Language ProcessingCode0
Clustering Prominent People and Organizations in Topic-Specific Text Corpora—0
Resource-Size matters: Improving Neural Named Entity Recognition with Optimized Large CorporaCode0
Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder—0
Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!Code0
Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations—0
Imparting Interpretability to Word Embeddings while Preserving Semantic StructureCode0
Evaluating Word Embeddings in Multi-label Classification Using Fine-grained Name TypingCode0
Clinical Text Classification with Rule-based Features and Knowledge-guided Convolutional Neural Networks—0
Tracking the Evolution of Words with Time-reflective Text Representations—0
Predicting Concreteness and Imageability of Words Within and Across Languages via Word EmbeddingsCode0
Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank ConcatenationCode0
Latent Semantic Analysis Approach for Document Summarization Based on Word Embeddings—0
A Review of Different Word Embeddings for Sentiment Classification using Deep LearningCode0
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