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Question

In the context of LSA, what is the benefit of using a subset of singular values for dimensionality reduction?

a.

It reduces the independence of the latent conceptual factors.

b.

It makes the analysis less suitable for Big Data requirements.

c.

It helps highlight interterm correlations for terms in a "semantic space."

d.

It increases the number of latent concepts identified.

Posted under Big Data Computing

Answer: (c).It helps highlight interterm correlations for terms in a "semantic space." Explanation:In the context of LSA, the benefit of using a subset of singular values for dimensionality reduction is that it helps highlight interterm correlations for terms in a "semantic space,".

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Q. In the context of LSA, what is the benefit of using a subset of singular values for dimensionality reduction?

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