如何计算两个向量的余弦相似度？ [英] How do I calculate the cosine similarity of two vectors?

问题描述

如何找到矢量之间的余弦相似度？

How do I find the cosine similarity between vectors?

我需要找到相似度来衡量两行文本之间的相关性。

I need to find the similarity to measure the relatedness between two lines of text.

例如，我有两个句子，如：

For example, I have two sentences like:

用户界面系统

system for user interface

用户界面机

...及其在tF-idf之后的各自向量，然后使用LSI进行标准化，例如
[1,0.5] 和 [0.5,1] 。

… and their respective vectors after tF-idf, followed by normalisation using LSI, for example [1,0.5] and [0.5,1].

我如何衡量这些向量之间的熟悉程度？

How do I measure the smiliarity between these vectors?

推荐答案

public class CosineSimilarity extends AbstractSimilarity {

  @Override
  protected double computeSimilarity(Matrix sourceDoc, Matrix targetDoc) {
    double dotProduct = sourceDoc.arrayTimes(targetDoc).norm1();
    double eucledianDist = sourceDoc.normF() * targetDoc.normF();
    return dotProduct / eucledianDist;
  }
}

我最近为我的信息做了一些tf-idf的东西大学检索单位。
我使用这个Cosine Similarity方法，该方法使用 Jama：Java Matrix Package 。

I did some tf-idf stuff recently for my Information Retrieval unit at University. I used this Cosine Similarity method which uses Jama: Java Matrix Package.

有关完整的源代码，请参阅 IR Math with Java：相似度量，非常好的资源，涵盖了很多不同的相似性度量。

For the full source code see IR Math with Java : Similarity Measures, really good resource that covers a good few different similarity measurements.

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