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  2. fastText - Wikipedia

    en.wikipedia.org/wiki/FastText

    fastText is a library for learning of word embeddings and text classification created by Facebook's AI Research (FAIR) lab. [3] [4] ...

  3. 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]

  4. Social media marketing - Wikipedia

    en.wikipedia.org/wiki/Social_media_marketing

    Social networking sites such as Facebook, Instagram, Twitter, MySpace etc. have all influenced the buzz of word of mouth marketing. In 1999, Misner said that word-of mouth marketing is, "the world's most effective, yet least understood marketing strategy" (Trusov, Bucklin, & Pauwels, 2009, p. 3). [72]

  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. Social network advertising - Wikipedia

    en.wikipedia.org/wiki/Social_network_advertising

    Social network advertising, also known as social media targeting, is a group of terms used to describe forms of online advertising and digital marketing that focus on social networking services. A significant aspect of this type of advertising is that advertisers can take advantage of users' demographic information , psychographics , and other ...

  7. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    IWE combines Word2vec with a semantic dictionary mapping technique to tackle the major challenges of information extraction from clinical texts, which include ambiguity of free text narrative style, lexical variations, use of ungrammatical and telegraphic phases, arbitrary ordering of words, and frequent appearance of abbreviations and acronyms ...

  8. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.

  9. Product placement - Wikipedia

    en.wikipedia.org/wiki/Product_placement

    [citation needed] Film productions need props for scenes, so each movie's property master, who is responsible for gathering props for the film, contacts advertising agencies or product companies directly. In addition to items for on-screen use, the product or service supplier might provide a production with complimentary products or services.

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