文档的词频-反向文档频率(TF-IDF)计算

TF-IDF计算：

TF-IDF反映了在文档集合中一个单词对一个文档的重要性，经常在文本数据挖据与信息

提取中用来作为权重因子。在一份给定的文件里，词频(termfrequency-TF)指的是某一

个给定的词语在该文件中出现的频率。逆向文件频率（inversedocument frequency，

IDF）是一个词语普遍重要性的度量。某一特定词语的IDF，可以由总文件数目除以包含

该词语之文件的数目，再将得到的商取对数得到。

相关代码：

private static Pattern r = Pattern.compile("([ \\t{}()\",:;. \n])");
private static List<String> documentCollection;

//Calculates TF-IDF weight for each term t in document d
private static float findTFIDF(String document, String term)
{
float tf = findTermFrequency(document, term);
float idf = findInverseDocumentFrequency(term);
return tf * idf;
}

private static float findTermFrequency(String document, String term)
{
int count = getFrequencyInOneDoc(document, term);

return (float)((float)count / (float)(r.split(document).length));
}

private static int getFrequencyInOneDoc(String document, String term)
{
int count = 0;
for(String s : r.split(document))
{
if(s.toUpperCase().equals(term.toUpperCase())) {
count++;
}
}
return count;
}

private static float findInverseDocumentFrequency(String term)
{
//find the  no. of document that contains the term in whole document collection
int count = 0;
for(String doc : documentCollection)
{
count += getFrequencyInOneDoc(doc, term);
}
/*
* log of the ratio of  total no of document in the collection to the no. of document containing the term
* we can also use Math.Log(count/(1+documentCollection.Count)) to deal with divide by zero case;
*/
return (float)Math.log((float)documentCollection.size() / (float)count);

}

建立文档的向量空间模型Vector Space Model并计算余弦相似度。

相关代码：

public static float findCosineSimilarity(float[] vecA, float[] vecB)
{
float dotProduct = dotProduct(vecA, vecB);
float magnitudeOfA = magnitude(vecA);
float magnitudeOfB = magnitude(vecB);
float result = dotProduct / (magnitudeOfA * magnitudeOfB);
//when 0 is divided by 0 it shows result NaN so return 0 in such case.
if (Float.isNaN(result))
return 0;
else
return (float)result;
}

public static float dotProduct(float[] vecA, float[] vecB)
{

float dotProduct = 0;
for (int i = 0; i < vecA.length; i++)
{
dotProduct += (vecA[i] * vecB[i]);
}

return dotProduct;
}

// Magnitude of the vector is the square root of the dot product of the vector with itself.
public static float magnitude(float[] vector)
{
return (float)Math.sqrt(dotProduct(vector, vector));
}

注意点：

零词过滤(stop-words filter)

零词列表

ftp://ftp.cs.cornell.edu/pub/smart/english.stop

关于TF-IDF参考这里：

链接–> http://en.wikipedia.org/wiki/Tf*idf