Use a hash set to track elements seen in `A` up to the current index, and another to track elements seen in `B` up to the current index. For each `i`, count the intersection of these two sets to determine `C[i]`.

Optimize the intersection check by maintaining a frequency map (or array) for elements in `A` and `B` up to the current index. For each `i`, iterate through the smaller of the two maps and count matches to compute `C[i]`.

Further optimize by using a single frequency array to track the count of elements that have appeared in both `A` and `B` up to the current index. Incrementally update this array as you traverse `A` and `B`, and use it to directly compute `C[i]` in constant time.