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  2. SECI model of knowledge dimensions - Wikipedia

    en.wikipedia.org/wiki/SECI_model_of_knowledge...

    Nonaka’s and Takeuchi’s SECI model is widely known and has achieved paradigmatic status. Perceived advantages of the model include: its appreciation of the dynamic nature of knowledge and knowledge creation. [5] it provides a framework for the management of the relevant processes. The model has also been much criticized at times. [7]

  3. Explicit knowledge - Wikipedia

    en.wikipedia.org/wiki/Explicit_knowledge

    Explicit knowledge (also expressive knowledge) [1] is knowledge that can be readily articulated, conceptualized, codified, formalized, stored and accessed. [2] It can be expressed in formal and systematical language and shared in the form of data, scientific formulae, specifications, manuals and such like. [3]

  4. SECI - Wikipedia

    en.wikipedia.org/wiki/SECI

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us

  5. Tacit knowledge - Wikipedia

    en.wikipedia.org/wiki/Tacit_knowledge

    Ikujiro Nonaka proposed a model of knowledge creation that explains how tacit knowledge can be converted to explicit knowledge, both of which can be converted into organisational knowledge. [16] While introduced by Nonaka in 1990, [ 17 ] the model was further developed by Hirotaka Takeuchi and is thus known as the Nonaka–Takeuchi model.

  6. Talk:SECI model of knowledge dimensions - Wikipedia

    en.wikipedia.org/wiki/Talk:SECI_model_of...

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  7. File:PAR model.pdf - Wikipedia

    en.wikipedia.org/wiki/File:PAR_model.pdf

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  8. PDF - Wikipedia

    en.wikipedia.org/wiki/PDF

    The original imaging model of PDF was opaque, similar to PostScript, where each object drawn on the page completely replaced anything previously marked in the same location. In PDF 1.4 the imaging model was extended to allow transparency. When transparency is used, new objects interact with previously marked objects to produce blending effects.

  9. 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 .

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