$1.2.$ Suppose we will classify patents about new battery technologies as either Li$-$ion or Li$-$metal. Below are titles of those patents. Please answer following questions $(20$pts$)$

$(--.)$

Preprocess titles $($apply stemming algorithm$)$ and convert these to word count vectors. $(4$pts$)$

$(,$

$)$

A:

Find the most simiar document with the first document by using the Euclidean distabce$-$based

similarity. $(3$pts$)$

$($

A: $5$

Find the most similar document with the third document by using the Eudidean distance$-$

based similarity $(3$ ts $)$

$()$

A: $2$

Assume that K$=2.$ Centorids are first and third documents. Do the clustering, show its results,

and interpret clusters. $(5$pts$)($K$-$means $$ K$2.$

$($initial centroid$)$

$.,$

$)$

A: $1(125),2(2,384)$

Classify a patent shown below into a corresponding cluster by using a text similarity measure.

$(5$pts$)$

$()$

$($Patent title$)$ Negative electrode for non$-$aqueous electrolyte secondary batteries, and non$-$

aqueous electrolyte secondary battery having the soild.

A : $2$

please solve the problems and show me detail.