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  2. OpenThesaurus - Wikipedia

    en.wikipedia.org/wiki/OpenThesaurus

    The cause for the start of the project was the arrival of OpenOffice.org in 2002, which was missing the thesaurus of its parent, StarOffice, due to its licensing.. OpenThesaurus filled that gap by importing possible synonyms from a freely available German/English dictionary and refining and updating these in crowdsourced work through the use of a web ap

  3. WordNet - Wikipedia

    en.wikipedia.org/wiki/WordNet

    WordNet is a lexical database of semantic relations between words that links words into semantic relations including synonyms, hyponyms, and meronyms.The synonyms are grouped into synsets with short definitions and usage examples.

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    mail.aol.com

    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  5. Category:Text-to-video generation - Wikipedia

    en.wikipedia.org/wiki/Category:Text-to-video...

    Text-to-video generation, such as text-to-video generators, generated videos etc. Pages in category "Text-to-video generation" The following 11 pages are in this category, out of 11 total.

  6. Thesaurus - Wikipedia

    en.wikipedia.org/wiki/Thesaurus

    Thesaurus Linguae Latinae. A modern english thesaurus. A thesaurus (pl.: thesauri or thesauruses), sometimes called a synonym dictionary or dictionary of synonyms, is a reference work which arranges words by their meanings (or in simpler terms, a book where one can find different words with similar meanings to other words), [1] [2] sometimes as a hierarchy of broader and narrower terms ...

  7. Reverso (language tools) - Wikipedia

    en.wikipedia.org/wiki/Reverso_(language_tools)

    In 2013 it released Reverso Context, a bilingual dictionary tool based on big data and machine learning algorithms. [5] In 2016 Reverso acquired Fleex, a service for learning English via subtitled movies. Based on content from Netflix, Fleex has expanded to also include video content from YouTube, TED Talks, and custom video files. [6] [7] [8]

  8. Text-to-video model - Wikipedia

    en.wikipedia.org/wiki/Text-to-video_model

    A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models .

  9. Co-occurrence network - Wikipedia

    en.wikipedia.org/wiki/Co-occurrence_network

    A co-occurrence network created with KH Coder. Co-occurrence network, sometimes referred to as a semantic network, [1] is a method to analyze text that includes a graphic visualization of potential relationships between people, organizations, concepts, biological organisms like bacteria [2] or other entities represented within written material.

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