Assignment:

Part $1$: $(3$ pages$)$

$-$ Take a set of $10$ documents

$-$ Classify these documents using TFIDF $+$ supervised learning

$-$ Use Bayesian to detect likelihood of usefulness

$-$ Use bayesian to establish relationships among these documents and representing them as a graph $($V$,$ E$)$

$$Provide pseudo code and diagram

Part $2$: $(3$ pages$)$

$-$ Take two parts of documents $($or two related documents$)$

$-$ Write a code to get extractive summarization using BOW approach

$-$ Combined two summaries using abstractive summarization

$-$ Model a document summarization approach for a huge documents using$-$ by parts extractive and later iteratively using abstractive at a time on a single pair.

$-$ Discuss advantages and disadvantages of this approach

$-$ Provide pseudo code and diagram