Three computers, A, B, and C, have the numerical features listed below: Feature Processor Speed (GHz) Disk Size (GB) Main-Memory Size (GB) A 1.75 750 6 B 2.68 480 4 C 3.56 330 6 We may imagine these values as defining a vector for each computer; for instance, A's vector is [1.75, 750, 6]. (1) If a certain user has an expectation vector of U = [2.43, 370, 5], calculate the cosine similarity between the user vector and each computer's vector. Explain which computer will be recommended to the user. Briefly justify yourself in one or two sentences. (2) If we compute the cosine similarity between any two of the vectors, the disk size will dominate and make differences in the other components essentially invisible. Design a data preprocessing method to cope with this problem. Briefly describe the steps of your method. (3) Calculate the cosine similarity between the user vector and each computer's vector after using your method and explain why your solution is effective.