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The use of different model parameters and different corpus sizes can greatly affect the quality of a word2vec model. Accuracy can be improved in a number of ways, including the choice of model architecture (CBOW or Skip-Gram), increasing the training data set, increasing the number of vector dimensions, and increasing the window size of words ...
Allows visual presentations from a DataObject to be cached. This allows an embedded object to store its visual representation, thus enabling it to be displayed later without needing to start the application that was used to create the object. Usually the stock implementation is used. OleCache2 Provides more fine-grained control over caching.
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]
Canva is an Australian multinational software company that provides a graphic design platform that provides tools for creating social media graphics, presentations, postcards, promotional merchandise and websites. [6] [7] [8] Launched in Australia in 2013, the service offers design tools for individuals and companies.
Unlike previous models, BERT is a deeply bidirectional, unsupervised language representation, pre-trained using only a plain text corpus. Context-free models such as word2vec or GloVe generate a single word embedding representation for each word in the vocabulary, whereas BERT takes into account the context for each occurrence of a given word ...
Ted Nelson gives a presentation on Project Xanadu, a theoretical hypertext model conceived in the 1960s whose first and incomplete implementation was first published in 1998. [6] In 1965, Ted Nelson coined the terms 'hypertext' and 'hypermedia' as part of a model he developed for creating and using linked content (first published reference 1965 ...
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