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：

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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：

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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)