TF

TF

TF-IDF

前言

前段时间，又具体看了自己以前整理的TF-IDF，这里把它发布在博客上，知识就是需要不断的重复的，否则就感觉生疏了。

TF-IDF理解

TF-IDF（term frequency–inverse document frequency）是一种用于资讯检索与资讯探勘的常用加权技术, TFIDF的主要思想是：如果某个词或短语在一篇文章中出现的频率TF高，并且在其他文章中很少出现，则认为此词或者短语具有很好的类别区分能力，适合用来分类。TFIDF实际上是：TF * IDF，TF词频(Term Frequency)，IDF反文档频率(Inverse Document Frequency)。TF表示词条在文档d中出现的频率。IDF的主要思想是：如果包含词条t的文档越少，也就是n越小，IDF越大，则说明词条t具有很好的类别区分能力。如果某一类文档C中包含词条t的文档数为m，而其它类包含t的文档总数为k，显然所有包含t的文档数n=m + k，当m大的时候，n也大，按照IDF公式得到的IDF的值会小，就说明该词条t类别区分能力不强。但是实际上，如果一个词条在一个类的文档中频繁出现，则说明该词条能够很好代表这个类的文本的特征，这样的词条应该给它们赋予较高的权重，并选来作为该类文本的特征词以区别与其它类文档。这就是IDF的不足之处.

TF公式：

IDF公式：

|D|：语料库中的文件总数

然后

TF-IDF实现（java）

这里采用了外部插件IKAnalyzer-2012.jar，用其进行分词

具体代码如下：

package tfidf;

import java.io.*;

import java.util.*;

import org.wltea.analyzer.lucene.IKAnalyzer;

public class ReadFiles {

/**

* @param args

*/

private static ArrayList FileList = new ArrayList();

// the list of file

//get list of file for the directory, including sub-directory of it

public static List readDirs(String filepath) throws FileNotFoundException, IOException

{

try

{

File file = new File(filepath);

if(!file.isDirectory())

{

System.out.println("输入的[]");

System.out.println("filepath:" + file.getAbsolutePath());

} else

{

String[] flist = file.list();

for (int i = 0; i < flist.length; i++)

{

File newfile = new File(filepath + "\\" + flist[i]);

if(!newfile.isDirectory())

{

FileList.add(newfile.getAbsolutePath());

} else if(newfile.isDirectory()) //if file is a directory, call ReadDirs

{

readDirs(filepath + "\\" + flist[i]);

}

}

}

}

catch(FileNotFoundException e)

{

System.out.println(e.getMessage());

}

return FileList;

}

//read file

public static String readFile(String file) throws FileNotFoundException, IOException

{

StringBuffer strSb = new StringBuffer();

//String is constant， StringBuffer can be changed.

InputStreamReader inStrR = new InputStreamReader(new FileInputStream(file), "gbk");

//byte streams to character streams

BufferedReader br = new BufferedReader(inStrR);

String line = br.readLine();

while(line != null){

strSb.append(line).append("\r\n");

line = br.readLine();

}

return strSb.toString();

}

//word segmentation

public static ArrayList cutWords(String file) throws IOException{

ArrayList words = new ArrayList();

String text = ReadFiles.readFile(file);

IKAnalyzer analyzer = new IKAnalyzer();

words = analyzer.split(text);

return words;

}

//term frequency in a file, times for each word

public static HashMap normalTF(ArrayList cutwords){

HashMap resTF = new HashMap();

for (String word : cutwords){

if(resTF.get(word) == null){

resTF.put(word, 1);

System.out.println(word);

} else{

resTF.put(word, resTF.get(word) + 1);

System.out.println(word.toString());

}

}

return resTF;

}

//term frequency in a file, frequency of each word

public static HashMap tf(ArrayList cutwords){

HashMap resTF = new HashMap();

int wordLen = cutwords.size();

HashMap intTF = ReadFiles.normalTF(cutwords);

Iterator iter = intTF.entrySet().iterator();

//iterator for that get from TF

while(iter.hasNext()){

Map.Entry entry = (Map.Entry)iter.next();

resTF.put(entry.getKey().toString(), float.parsefloat(entry.getValue().toString()) / wordLen);

System.out.println(entry.getKey().toString() + " = "+ float.parsefloat(entry.getValue().toString()) / wordLen);

}

return resTF;

}

//tf times for file

public static HashMap> normalTFAllFiles(String dirc) throws IOException{

HashMap> allNormalTF = new HashMap>();

List filelist = ReadFiles.readDirs(dirc);

for (String file : filelist){

HashMap dict = new HashMap();

ArrayList cutwords = ReadFiles.cutWords(file);

//get cut word for one file

dict = ReadFiles.normalTF(cutwords);

allNormalTF.put(file, dict);

}

return allNormalTF;

}

//tf for all file

public static HashMap> tfAllFiles(String dirc) throws IOException{

HashMap> allTF = new HashMap>();

List filelist = ReadFiles.readDirs(dirc);

for (String file : filelist){

HashMap dict = new HashMap();

ArrayList cutwords = ReadFiles.cutWords(file);

//get cut words for one file

dict = ReadFiles.tf(cutwords);

allTF.put(file, dict);

}

return allTF;

}

public static HashMap idf(HashMap> all_tf){

HashMap resIdf = new HashMap();

HashMap dict = new HashMap();

int docNum = FileList.size();

for (int i = 0; i < docNum; i++){

HashMap temp = all_tf.get(FileList.get(i));

Iterator iter = temp.entrySet().iterator();

while(iter.hasNext()){

Map.Entry entry = (Map.Entry)iter.next();

String word = entry.getKey().toString();

if(dict.get(word) == null){

dict.put(word, 1);

} else {

dict.put(word, dict.get(word) + 1);

}

}

}

System.out.println("IDF for every word is:");

Iterator iter_dict = dict.entrySet().iterator();

while(iter_dict.hasNext()){

Map.Entry entry = (Map.Entry)iter_dict.next();

float value = (float)Math.log(docNum / float.parsefloat(entry.getValue().toString()));

resIdf.put(entry.getKey().toString(), value);

System.out.println(entry.getKey().toString() + " = " + value);

}

return resIdf;

}

public static void tf_idf(HashMap> all_tf,HashMap idfs){

HashMap> resTfIdf = new HashMap();

int docNum = FileList.size();

for (int i = 0; i < docNum; i++){

String filepath = FileList.get(i);

HashMap tfidf = new HashMap();

HashMap temp = all_tf.get(filepath);

Iterator iter = temp.entrySet().iterator();

while(iter.hasNext()){

Map.Entry entry = (Map.Entry)iter.next();

String word = entry.getKey().toString();

float value = (float)float.parsefloat(entry.getValue().toString()) * idfs.get(word);

tfidf.put(word, value);

}

resTfIdf.put(filepath, tfidf);

}

System.out.println("TF-IDF for Every file is :");

DisTfIdf(resTfIdf);

}

public static void DisTfIdf(HashMap> tfidf){

Iterator iter1 = tfidf.entrySet().iterator();

while(iter1.hasNext()){

Map.Entry entrys = (Map.Entry)iter1.next();

System.out.println("FileName: " + entrys.getKey().toString());

System.out.print("{");

HashMap temp = (HashMap) entrys.getValue();

Iterator iter2 = temp.entrySet().iterator();

while(iter2.hasNext()){

Map.Entry entry = (Map.Entry)iter2.next();

System.out.print(entry.getKey().toString() + " = " + entry.getValue().toString() + ", ");

}

System.out.println("}");

}

}

public static void main(String[] args) throws IOException {

// TODO Auto-generated method stub

String file = "D:/testfiles";

HashMap> all_tf = tfAllFiles(file);

System.out.println();

HashMap idfs = ihttp://df(all_tf);

System.out.println();

tf_idf(all_tf, idfs);

}

}

结果如下图：

常见问题

没有加入lucene jar包

lucene包和je包版本不适合

总结

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