Big data similarities: Matrix of signatures

Consider big data that cannot be loaded on memory.

A row in a bit vector denotes a shingle, and a column is a data set, e.g., a document. Consider the following bit vector. O AWNO S1 S2 S3 S4 0 1 1 0 0 0 0 1 1 1 0 0 1 3 0 0 1 0 4 1 1 1 0 5 0 1 1 0 6 1 0 0 0 1) Apply Jaccard similarity function to the bit vector above. Find sim(S1, S2), sim(S2, S3), sim(S1, S4). 2) Using the following hash functions, generate a matrix of signatures. Show the result for each step. h1(x) = x+1 MOD 5 h2(x) = 2x +3 MOD 4 h3(x) = 3x + 2 MOD 4 Note that the output signature matrix has three rows. 3) Find sim(S1, S2), sim(S2, S3), sim(S1, S4) using the Jaccard similarity function. 4) Compare the similarities obtained between Q1 and Q3. Which matrix would be better