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  2. Word embedding - Wikipedia

    en.wikipedia.org/wiki/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 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. [1]

  3. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The idea of skip-gram is that the vector of a word should be close to the vector of each of its neighbors. The idea of CBOW is that the vector-sum of a word's neighbors should be close to the vector of the word. In the original publication, "closeness" is measured by softmax, but the framework allows other ways to measure closeness.

  4. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    Word2vec is a word embedding technique which learns to represent words through self-supervision over each word and its neighboring words in a sliding window across a large corpus of text. [28] The model has two possible training schemes to produce word vector representations, one generative and one contrastive. [ 27 ]

  5. Sentence embedding - Wikipedia

    en.wikipedia.org/wiki/Sentence_embedding

    An alternative direction is to aggregate word embeddings, such as those returned by Word2vec, into sentence embeddings. The most straightforward approach is to simply compute the average of word vectors, known as continuous bag-of-words (CBOW). [9] However, more elaborate solutions based on word vector quantization have also been proposed.

  6. Vectorization - Wikipedia

    en.wikipedia.org/wiki/Vectorization

    Automatic vectorization, a compiler optimization that transforms loops to vector operations; Image tracing, the creation of vector from raster graphics; Word embedding, mapping words to vectors, in natural language processing

  7. NYT ‘Connections’ Hints and Answers Today, Wednesday, January 15

    www.aol.com/nyt-connections-hints-answers-today...

    If you've been having trouble with any of the connections or words in Wednesday's puzzle, you're not alone and these hints should definitely help you out. Plus, I'll reveal the answers further ...

  8. Explicit semantic analysis - Wikipedia

    en.wikipedia.org/wiki/Explicit_semantic_analysis

    Mathematically, this list is an N-dimensional vector of word-document scores, where a document not containing the query word has score zero. To compute the relatedness of two words, one compares the vectors (say u and v ) by computing the cosine similarity,

  9. Far-left Antifa activists waiting to see Trump actions. How ...

    www.aol.com/far-left-antifa-activists-waiting...

    Buoyed by promised pardons of their brethren for their Jan. 6 crimes and by Trump’s embrace of popular extremist far-right figures, those groups will likely see a resurgence after January ...