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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 1551–1575 of 4002 papers

TitleStatusHype
Which Evaluations Uncover Sense Representations that Actually Make Sense?—0
FlorUniTo@TRAC-2: Retrofitting Word Embeddings on an Abusive Lexicon for Aggressive Language Detection—0
Graph Exploration and Cross-lingual Word Embeddings for Translation Inference Across Dictionaries—0
Automatic Term Extraction from Newspaper Corpora: Making the Most of Specificity and Common Features—0
Automatic Creation of Correspondence Table of Meaning Tags from Two Dictionaries in One Language Using Bilingual Word Embedding—0
Translating Knowledge Representations with Monolingual Word Embeddings: the Case of a Thesaurus on Corporate Non-Financial Reporting—0
Combining Character and Word Embeddings for the Detection of Offensive Language in Arabic—0
Extrapolating Binder Style Word Embeddings to New Words—0
FRAQUE: a FRAme-based QUEstion-answering system for the Public Administration domain—0
Line-a-line: A Tool for Annotating Word-Alignments—0
Legal-ES: A Set of Large Scale Resources for Spanish Legal Text Processing—0
Evaluating Word Embeddings for Indonesian--English Code-Mixed Text Based on Synthetic Data—0
OSACT4 Shared Tasks: Ensembled Stacked Classification for Offensive and Hate Speech in Arabic Tweets—0
Building Sense Representations in Danish by Combining Word Embeddings with Lexical Resources—0
Sentiment Analysis for Hinglish Code-mixed Tweets by means of Cross-lingual Word Embeddings—0
BUCC2020: Bilingual Dictionary Induction using Cross-lingual Embedding—0
Mining Semantic Relations from Comparable Corpora through Intersections of Word Embeddings—0
French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus—0
``A Passage to India'': Pre-trained Word Embeddings for Indian Languages—0
Voting for POS tagging of Latin texts: Using the flair of FLAIR to better Ensemble Classifiers by Example of Latin—0
Does History Matter? Using Narrative Context to Predict the Trajectory of Sentence Sentiment—0
Distributional Semantics for Neo-Latin—0
A Gradient Boosting-Seq2Seq System for Latin POS Tagging and Lemmatization—0
Usability and Accessibility of Bantu Language Dictionaries in the Digital Age: Mobile Access in an Open Environment—0
LMU Bilingual Dictionary Induction System with Word Surface Similarity Scores for BUCC 2020—0
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