GMU:Critical VR Lab I/F.Z.Ayguler: Difference between revisions

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https://www.youtube.com/watch?v=lURd37SiN6Y&feature=youtu.be

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CRITICAL VR PROJECT

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I choose a literary work of Jean Baudrillard- Simulacra and Simulation. I used the gensim library’s Word2Vec model to get word-embedding vectors for each word. Word2Vec is used to compute the similarity between words from a large corpus of text. The algorithm is very good at finding most similar words (nearest neighbors), I also tried subtracting and adding words. I am giving an examples to show how the program functions.

[[File:simularca.png|700px]]

This is the graphic which is reduced the dimensions of the Word2Vec space down to x and y coordinates. Every dot represents a word. Dots that are closer together in a space mean that they are similar.

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 https://www.youtube.com/watch?v=lURd37SiN6Y&feature=youtu.be
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 CRITICAL VR PROJECT
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 I choose a literary work of Jean Baudrillard- Simulacra and Simulation. I used the gensim library’s Word2Vec model to get word-embedding vectors for each word. Word2Vec is used to compute the similarity between words from a large corpus of text. The algorithm is very good at finding most similar words (nearest neighbors), I also tried subtracting and adding words. I am giving an examples to show how the program functions.
+[[File:simularca.png|700px]]
+This is the graphic which is reduced the dimensions of the Word2Vec space down to x and y coordinates. Every dot represents a word. Dots that are closer together in a space mean that they are similar.