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Everything about Word2Vec
Models used to produce word embeddings
In natural language processing, Word2Vec is a technique for obtaining vector representations of words as word embeddings. These vectors capture information about the meaning of a word based on its surrounding words in a piece of text, following the principles of distributional semantics. Once trained, the model can be used to find words with similar meanings or usage, while its embeddings can serve as inputs to systems for search and classification. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Word2VecA 5-minute orientation
- Skim a recent paper: Sentiment Classification: Review of Text Vectorization Methods: Bag of Words, Tf-Idf, Word2vec and Doc2vecInfluential work since 2022
- Pick up a classic book: Wissensbasiertes IT-Projektmanagement Mit KI- und Cloud-TechnikenThe most-reprinted book on the subject
- Read the landmark paper: Word2VecCited 995 times
- Go sideways: Word embeddingA closely related topic
- Go sideways: Tomáš MikolovA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Word2Vec
Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model
Bi-LSTM Model to Increase Accuracy in Text Classification: Combining Word2vec CNN and Attention Mechanism
Chinese comments sentiment classification based on word2vec and SVMperf
Beyond Word2vec: An approach for urban functional region extraction and identification by combining Place2vec and POIs
Word2Vec Model Analysis for Semantic Similarities in English Words
Word2vec convolutional neural networks for classification of news articles and tweets
A detailed review on word embedding techniques with emphasis on word2vec
🆕 Influential since 2022
Sentiment Classification: Review of Text Vectorization Methods: Bag of Words, Tf-Idf, Word2vec and Doc2vec
Word2Vec and LSTM based deep learning technique for context-free fake news detection
Investigating response behavior through TF-IDF and Word2vec text analysis: A case study of PISA 2012 problem-solving process data
LogUAD: Log Unsupervised Anomaly Detection Based on Word2Vec
iACVP: markedly enhanced identification of anti-coronavirus peptides using a dataset-specific word2vec model
📚 Books worth reading
- 📕Wissensbasiertes IT-Projektmanagement Mit KI- und Cloud-TechnikenJan Peter Schagen, Ganen Sethupathy · 2024
- 📕Knowledge-Based Project Management with the Help of AI and Cloud TechniquesStephan Zelewski, Ganen Sethupathy · 2024
Fundamentals of Deep LearningNikhil Buduma · 2017
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Word embedding In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis. Typically, the representation is…
- 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…
- FastText fastText is an open-source library developed by Facebook AI Research (FAIR) for learning word representations and performing text classification. It was…
- GloVe In natural language processing, GloVe (acronym for Global Vectors) is a model for distributed word representation. The model is an unsupervised learning…
- 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…
- 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…
- Language model A language model is a computational model that predicts sequences in natural language. Language models are useful for a variety of tasks, including speech…
- Paraphrasing (computational linguistics) Paraphrase or paraphrasing in computational linguistics is the natural language processing task of detecting and generating paraphrases. Applications of…