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for key1 in user1:
for key2 in user2:
if key1[0] == key2[0]:
sum_xy +=(key1[1] - avg_x) * (key2[1] - avg_y)
sum_y +=(key2[1] - avg_y) * (key2[1] -avg_y)
sum_x +=(key1[1] - avg_x) * (key1[1] - avg_x)
if sum_xy == 0.0:
return 0
sx_sy=math.sqrt(sum_x) * math.sqrt(sum_y)
这个函数里面的相似度计算应该是这样吧, userFC.py
如果将两个文本内容分别进行hash后,比较hash结果, 那怎么hash的相似度就能直接反应了文本内容的相似度?
建立一个集合(S1,S2...Sn)与哈希函数(H1,H2...Hn)的新矩阵T,并将每个元素初始值定义为无穷大
对于任何一列的集合,如果T(Hi,Sj)为0,则什么都不做
对于任何一列的集合,如果T(Hi,Sj)不为0,则将T(Hi,Sj)和当前值比较,更新为较小的值。
请问如何解释这个符号T(Hi,Sj)的运算规则是什么呢 ? 没看懂
麻烦大佬 能解释下不
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