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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 3326–3350 of 4002 papers

TitleStatusHype
Word Sense Filtering Improves Embedding-Based Lexical Substitution—0
Clustering of Russian Adjective-Noun Constructions using Word Embeddings—0
An RNN-based Binary Classifier for the Story Cloze Test—0
Improving Verb Metaphor Detection by Propagating Abstractness to Words, Phrases and Individual Senses—0
Using bilingual word-embeddings for multilingual collocation extraction—0
Arabic POS Tagging: Don't Abandon Feature Engineering Just Yet—0
Automated WordNet Construction Using Word EmbeddingsCode0
Supervised and Unsupervised Word Sense Disambiguation on Word Embedding Vectors of Unambigous Synonyms—0
Potential and Limitations of Cross-Domain Sentiment Classification—0
Centroid-based Text Summarization through Compositionality of Word EmbeddingsCode0
Comparison of Short-Text Sentiment Analysis Methods for Croatian—0
Social Bias in Elicited Natural Language InferencesCode0
Elucidating Conceptual Properties from Word Embeddings—0
Arabic Textual Entailment with Word Embeddings—0
A Twitter Corpus and Benchmark Resources for German Sentiment Analysis—0
Semantic Similarity of Arabic Sentences with Word Embeddings—0
Using Linked Disambiguated Distributional Networks for Word Sense Disambiguation—0
Integrating Semantic Knowledge into Lexical Embeddings Based on Information Content MeasurementCode0
Literal or idiomatic? Identifying the reading of single occurrences of German multiword expressions using word embeddings—0
Cross-Lingual Syntactically Informed Distributed Word Representations—0
Multivariate Gaussian Document Representation from Word Embeddings for Text Categorization—0
Modelling metaphor with attribute-based semantics—0
Reranking Translation Candidates Produced by Several Bilingual Word Similarity Sources—0
Using Word Embedding for Cross-Language Plagiarism Detection—0
Ranking Convolutional Recurrent Neural Networks for Purchase Stage Identification on Imbalanced Twitter Data—0
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