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  2. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The CBOW can be viewed as a ‘fill in the blank’ task, where the word embedding represents the way the word influences the relative probabilities of other words in the context window. Words which are semantically similar should influence these probabilities in similar ways, because semantically similar words should be used in similar contexts.

  3. Help:WordToWiki - Wikipedia

    en.wikipedia.org/wiki/Help:WordToWiki

    Open your document in Word, and "save as" an HTML file. Open the HTML file in a text editor and copy the HTML source code to the clipboard. Paste the HTML source into the large text box labeled "HTML markup:" on the html to wiki page. Click the blue Convert button at the bottom of the page.

  4. 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]

  5. Help:Creation and usage of media files - Wikipedia

    en.wikipedia.org/wiki/Help:Creation_and_usage_of...

    Allows embed code to reference a segment of the video stream or set a start time. Hover over the player to see start time listed as 5s, press play and notice it stops playback at 7 seconds. [[File:Weeding.ogv|thumb|300px|start=5|end=7|Starts at 5 seconds and ends playback at 7 seconds]] One can also use MM:SS or HH:MM:SS format for start and end.

  6. WordNet - Wikipedia

    en.wikipedia.org/wiki/WordNet

    The database contains 155,327 words organized in 175,979 synsets for a total of 207,016 word-sense pairs; in compressed form, it is about 12 megabytes in size. [ 3 ] It includes the lexical categories nouns , verbs , adjectives and adverbs but ignores prepositions , determiners and other function words.

  7. Sentence embedding - Wikipedia

    en.wikipedia.org/wiki/Sentence_embedding

    In practice however, BERT's sentence embedding with the [CLS] token achieves poor performance, often worse than simply averaging non-contextual word embeddings. SBERT later achieved superior sentence embedding performance [8] by fine tuning BERT's [CLS] token embeddings through the usage of a siamese neural network architecture on the SNLI dataset.

  8. Object Linking and Embedding - Wikipedia

    en.wikipedia.org/wiki/Object_Linking_and_Embedding

    Object Linking and Embedding (OLE) is a proprietary technology developed by Microsoft that allows embedding and linking to documents and other objects. For developers, it brought OLE Control Extension (OCX), a way to develop and use custom user interface elements.

  9. Controlled vocabulary - Wikipedia

    en.wikipedia.org/wiki/Controlled_vocabulary

    Well known thesauri include the Art and Architecture Thesaurus and the ERIC Thesaurus. When selecting terms for a controlled vocabulary, the designer has to consider the specificity of the term chosen, whether to use direct entry, inter consistency and stability of the language.

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