Given the following 4 documents retrieved from the collection of 10,000,000 documents in response to query "NP A Turing a circuits": D1="deterministic Turing machines are special non-deterministic Turing machines, it is easily observed that each problem in P is also member of the class NP." D2="also known that if P = NP, then EXPTIME = NEXPTIME, the class of problems solvable in exponential time by a nondeterministic Turing machine" D3="In computational complexity theory, an advice string is an extra input to a Turing machine. A circuit A(n) is deciding the problem, or we can use a Turing machine that interprets the advice string as a description of the circuit" D4="The fact that Circuit-SAT is in NP is easy. Given a circuit C in the standard basis" We know that document frequency of terms NP, circuit and Turing in this collection are 100,000 and 50,000 and 200,000 respectively. Use sublinear scaling weighted term frequency wft,a, wf-idf metric and cosine similarity measure to compute ranking of each document w.r.t the query. Then order documents according to the rank. Use format of the table 6.1 on page 121 to show intermediate computations (required for getting credit) word digital video cameras query document tf wf df idf qi = wf-idf tf wf d; = normalized wf giud; 10,000 100,000 50,000 Table 6.1 Cosine computation for Exercise 6.19. Given the following 4 documents retrieved from the collection of 10,000,000 documents in response to query "NP A Turing a circuits": D1="deterministic Turing machines are special non-deterministic Turing machines, it is easily observed that each problem in P is also member of the class NP." D2="also known that if P = NP, then EXPTIME = NEXPTIME, the class of problems solvable in exponential time by a nondeterministic Turing machine" D3="In computational complexity theory, an advice string is an extra input to a Turing machine. A circuit A(n) is deciding the problem, or we can use a Turing machine that interprets the advice string as a description of the circuit" D4="The fact that Circuit-SAT is in NP is easy. Given a circuit C in the standard basis" We know that document frequency of terms NP, circuit and Turing in this collection are 100,000 and 50,000 and 200,000 respectively. Use sublinear scaling weighted term frequency wft,a, wf-idf metric and cosine similarity measure to compute ranking of each document w.r.t the query. Then order documents according to the rank. Use format of the table 6.1 on page 121 to show intermediate computations (required for getting credit) word digital video cameras query document tf wf df idf qi = wf-idf tf wf d; = normalized wf giud; 10,000 100,000 50,000 Table 6.1 Cosine computation for Exercise 6.19