一些nlp相关算法的实现
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在计算相似度得分的时候，为什么需要除分母所示的那一部分？
首先感谢您提供的代码，谢谢！
score += (self.idf[word]*self.f[index][word]*(self.k1+1) / (self.f[index][word]+self.k1*(1-self.b+self.b*d / self.avgdl)))
如代码所示，正常计算tf-idf的时候tf与idf相乘直接即可，不是很清楚为什么需要再除下面的部分？
如果可以的话，能麻烦您解释一下嘛？
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