文档的词频-反向文档频率(TF-IDF)计算
- - CSDN博客推荐文章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. 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.
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