
    Given an event's social engagement score, determine the maximum potential engagement value by either keeping the event as a single recommendation or splitting it into smaller event clusters of 1/2, 1/3, 1/4, and 1/5 of the original size and combining their respective engagement values. For each event cluster, recursively apply the same decision process to maximize the total engagement score.
    

    
def get_max_sum(n):
    """
    Given an event's social engagement score, determine the maximum potential engagement value by either keeping the event as a single recommendation or splitting it into smaller event clusters of 1/2, 1/3, 1/4, and 1/5 of the original size and combining their respective engagement values. For each event cluster, recursively apply the same decision process to maximize the total engagement score.
    

    """
def get_max_sum(n):
    """
    Given an event's social engagement score, determine the maximum potential engagement value by either keeping the event as a single recommendation or splitting it into smaller event clusters of 1/2, 1/3, 1/4, and 1/5 of the original size and combining their respective engagement values. For each event cluster, recursively apply the same decision process to maximize the total engagement score.
    

    """
    res = list()
    res.append(0)
    res.append(1)
    i = 2
    while i < n + 1:
        res.append(max(i, res[int(i / 2)] + res[int(i / 3)] + res[int(i / 4)] + res[int(i / 5)]))
        i = i + 1
    return res[n]