/smart-legal-analytics

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2) py -3.7 .\summarization.py

--> Summarize the documents using TextRank, Luhn, LSA, LexRank, KL-Sum, SumBasic, Random, and Reduction

3) py -3.7 .\knapsack.py

--> Summarize the documents using the proposed knapsack algorithm

4) py -3.7 .\similarity_matrix_formation.py

--> Form a similarity matrix for the different cases

5) py -3.7 .\similarity_ranking_csv.py

--> Rank the similarity matrices row-wise

6) py -3.7 .\top_k_analysis.py

--> Plots the required graphs