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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 2551–2575 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
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