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Unlocking Concept Measurement. How the analogy-completion task changed… | by Danielle Boccelli | Aug, 2024

August 2, 2024
in Artificial Intelligence
Reading Time: 2 mins read
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Photograph by Eugene Golovesov on Unsplash

How the analogy-completion job modified phrase illustration

Danielle Boccelli
Towards Data Science

This essay goals to debate the event of the word2vec and GloVe algorithms because it pertains to a secondary function for which these algorithms have been utilized: the evaluation of ideas contained inside textual content corpora. First, the word2vec algorithm is mentioned in mild of its historic context. Then, the analogy-completion job that highlighted the potential of the semantic arithmetic doable with word2vec embeddings is described. Lastly, the event of the GloVe algorithm is contrasted with the word2vec algorithm.

The word2vec algorithm (Mikolov et al., 2013a) combines two foremost technical insights: (1) steady vectors can be utilized to symbolize semantic data (2) and the inner representations discovered by neural networks are conceptually significant. When the algorithm was launched in 2013, nevertheless, neither the continual illustration of semantic data nor the conceptual worth of inside representations have been new concepts. Extra particularly, within the data retrieval area, latent semantic evaluation (LSA; Deerwester et al., 1990) and latent Dirichlet allocation (Blei et al., 2003) have been proposed as statistical strategies that leverage the semantic data latent in texts to enhance upon strategies that handled phrases as indexical options (that exist…

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Tags: analogycompletionAugBoccellichangedConceptDanielleMeasurementTaskUnlocking
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