information. The preprocessed text is then transformed into a feature$-$rich representation using a chosen vectorization method for further use in the application to perform similarity analysis.

Part I

Sentence cmpletion using N$-$gram:

Recommend the top $3$ words to complete the given sentence using $N-$gram language model. The goal is to demonstrate the relevance of recommended words based on the occurrence of Trigram within the corpus. Use all the instances in the dataset as a training corpus.

Test Sentence: disappointed, and unsatisfied.

Part II

Perform the below sequential tasks on the given dataset.

i$)$ Text Preprocessing: $(2$ Marks$)$

Tokenization

Lowercasing

Stop Words Removal