一个有关协同过滤推荐系统的代码问题

def userSimilarityBest(self,train = None):
train = train or self.traindata
self.userSimBest = dict()
item_users = dict()
for u,item in train.items():
for i in item.keys():
item_users.setdefault(i,set())
item_users[i].add(u)
user_item_count = dict()
count = dict()
for item,users in item_users.items():
for u in users:
user_item_count.setdefault(u,0)
user_item_count[u] += 1
for v in users:
if u == v:continue
count.setdefault(u,{})
count[u].setdefault(v,0)
count[u][v] += 1
for u ,related_users in count.items():
self.userSimBest.setdefault(u,dict())
for v, cuv in related_users.items():
self.userSimBest[u][v] = cuv / math.sqrt(user_item_count[u] * user_item_count[v] * 1.0)
这里面的代码：
count[u][v] += 1
表示的是什么意思啊？为什么右边的那个增量要用1啊。
我是新人，刚学的Python，不懂啊。求个个大神解答。谢谢了啊。