Task $2$b $-$ More understanding of Semantic Matching $(15$ points$).$

Which terms does LSI find similar?

To understand why the LSI$-$expanded vectors get the results they do$,$ we're going to look at what the operator $$

does to text. In particular, the term$-$term matrix $$

tells us the term expansion behavior of this LSI model. Think of the term$-$term matrix like an operator that first maps a term to the latent space $$

$($using $$

$),$ then back again from $$

to term space $($using $$

transpose$).$ The $(,)$

entry of $$

is a kind of association weight between term $$

and term $$

$.$

Write a function to get the most related terms $($according to LSI$)$ for the word "economy". To do this:

Compute the term$-$term matrix from the matrix U $($the reduced$\_$term$\_$matrix variable$).$

Use the term$-$term matrix to get the association weights of all words related to the term "economy"

Sort by descending weight value.

Your function should return the top $5$ words and their weights as a list of $($string$,$ float$)$ tuples.

Do the related terms match your subjective similarity judgment?