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Everything about Word embedding
Method in natural language processing
In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis. Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. Word embeddings can be obtained using language modeling and feature learning techniques, where words or phrases from the vocabulary are mapped to vectors of real numbers. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Word embeddingA 5-minute orientation
- Skim a recent paper: Impact of word embedding models on text analytics in deep learning environment: a reviewInfluential work since 2022
- Pick up a classic book: Tales of Mystery and Imagination [29 stories]The most-reprinted book on the subject
- Read the landmark paper: How to Generate a Good Word EmbeddingCited 260 times
- Go sideways: Word2VecA closely related topic
- Go sideways: Sentence embeddingA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
How to Generate a Good Word Embedding
Text document summarization using word embedding
Citation Intent Classification Using Word Embedding
Content Tree Word Embedding for document representation
ACTUARIAL APPLICATIONS OF WORD EMBEDDING MODELS
Word Sense Disambiguation for Arabic Exploiting Arabic WordNet and Word Embedding
Bayesian Neural Word Embedding
Morphological Word Embedding for Arabic
🆕 Influential since 2022
Impact of word embedding models on text analytics in deep learning environment: a review
Word Embeddings: What Works, What Doesn’t, and How to Tell the Difference for Applied Research
A detailed review on word embedding techniques with emphasis on word2vec
Semantic projection recovers rich human knowledge of multiple object features from word embeddings
Deep-STP: a deep learning-based approach to predict snake toxin proteins by using word embeddings
📚 Books worth reading
Tales of Mystery and Imagination [29 stories]Edgar Allan Poe · 1902
JavaScriptDavid Flanagan · 1996
Born to talkLloyd M. Hulit, Merle R. Howard · 1992
Tales of Mystery and Terror (Black Cat / Descent into the Maelstrom / Fall of the House of Usher / Hop-Frog / Masque of the Red Death / MS. Found in a Bottle / Oblong Box / Oval Portrait / Pit and the Pendulum / Some Words With a Mummy / Sphinx / Tell-Tale Heart / William Wilson)Edgar Allan Poe · 1967
Tales of Mystery, Imagination, & Humour, and Poems [8 stories, 11 poems]Edgar Allan Poe · 1852
The Works of Edgar Allan Poe [68 stories, 31 poems]Edgar Allan Poe · 1985
John Searle's Philosophy of LanguageSavas L. Tsohatzidis · 2007
What every engineer should know about ExcelJ. P. Holman · 2006
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Word2Vec In natural language processing, Word2Vec is a technique for obtaining vector representations of words as word embeddings. These vectors capture information…
- Sentence embedding In natural language processing, a sentence embedding (or document embedding) is a representation of a natural language text as a vector of numbers which…
- Tomáš Mikolov Tomáš Mikolov is a Czech computer scientist known for his work on neural language models and word representations. He was the lead author of the 2013 paper…
- BERT (language model) Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. It learns to represent…
- Distributional semantics Distributional semantics is a research area that develops and studies theories and methods for quantifying and categorizing semantic similarities between…
- GloVe In natural language processing, GloVe (acronym for Global Vectors) is a model for distributed word representation. The model is an unsupervised learning…
- Latent space A latent space, also known as a latent feature space or embedding space, is an embedding of a set of items within a manifold in which similar items are…
- FastText fastText is an open-source library developed by Facebook AI Research (FAIR) for learning word representations and performing text classification. It was…