TF-IDF理解及其Java实现

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：

$\mathrm{tf_{i,j}} = \frac{n_{i,j}}{\sum_k n_{k,j}}$

以上式子中 $n_{i,j}$ 是该词在文件 $d_{j}$ 中的出现次数，而分母则是在文件 $d_{j}$ 中所有字词的出现次数之和。

IDF公式：

$\mathrm{idf_{i}} = \log \frac{|D|}{|\{j: t_{i} \in d_{j}\}|}$

|D|：语料库中的文件总数
$|\{ j: t_{i} \in d_{j}\}|$ ：包含词语 $t_{i}$ 的文件数目（即 $n_{i,j} \neq 0$ 的文件数目）如果该词语不在语料库中，就会导致被除数为零，因此一般情况下使用 $1 + |\{j : t_{i} \in d_{j}\}|$

然后

$\mathrm{tf{}idf_{i,j}} = \mathrm{tf_{i,j}} \times \mathrm{idf_{i}}$

TF-IDF案例

案例：假如一篇文件的总词语数是100个，而词语“母牛”出现了3次，那么“母牛”一词在该文件中的词频就是3/100=0.03。一个计算文件频率 (DF) 的方法是测定有多少份文件出现过“母牛”一词，然后除以文件集里包含的文件总数。所以，如果“母牛”一词在1,000份文件出现过，而文件总数是10,000,000份的话，其逆向文件频率就是 lg(10,000,000 / 1,000)=4。最后的TF-IDF的分数为0.03 * 4=0.12。

TF-IDF实现（Java）

这里采用了外部插件IKAnalyzer-2012.jar，用其进行分词，插件和测试文件可以从这里下载：点击

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<String> FileList = new ArrayList<String>(); // the list of file//get list of file for the directory, including sub-directory of itpublic static List<String> 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 filepublic 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 streamsBufferedReader br = new BufferedReader(inStrR); String line = br.readLine();while(line != null){strSb.append(line).append("\r\n");line = br.readLine();    }return strSb.toString();}//word segmentationpublic static ArrayList<String> cutWords(String file) throws IOException{ArrayList<String> words = new ArrayList<String>();String text = ReadFiles.readFile(file);IKAnalyzer analyzer = new IKAnalyzer();words = analyzer.split(text);return words;}//term frequency in a file, times for each wordpublic static HashMap<String, Integer> normalTF(ArrayList<String> cutwords){HashMap<String, Integer> resTF = new HashMap<String, Integer>();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 wordpublic static HashMap<String, Float> tf(ArrayList<String> cutwords){HashMap<String, Float> resTF = new HashMap<String, Float>();int wordLen = cutwords.size();HashMap<String, Integer> intTF = ReadFiles.normalTF(cutwords); Iterator iter = intTF.entrySet().iterator(); //iterator for that get from TFwhile(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 filepublic static HashMap<String, HashMap<String, Integer>> normalTFAllFiles(String dirc) throws IOException{HashMap<String, HashMap<String, Integer>> allNormalTF = new HashMap<String, HashMap<String,Integer>>();List<String> filelist = ReadFiles.readDirs(dirc);for(String file : filelist){HashMap<String, Integer> dict = new HashMap<String, Integer>();ArrayList<String> cutwords = ReadFiles.cutWords(file); //get cut word for one file
            dict = ReadFiles.normalTF(cutwords);allNormalTF.put(file, dict);}    return allNormalTF;}//tf for all filepublic static HashMap<String,HashMap<String, Float>> tfAllFiles(String dirc) throws IOException{HashMap<String, HashMap<String, Float>> allTF = new HashMap<String, HashMap<String, Float>>();List<String> filelist = ReadFiles.readDirs(dirc);for(String file : filelist){HashMap<String, Float> dict = new HashMap<String, Float>();ArrayList<String> cutwords = ReadFiles.cutWords(file); //get cut words for one file
            dict = ReadFiles.tf(cutwords);allTF.put(file, dict);}return allTF;}public static HashMap<String, Float> idf(HashMap<String,HashMap<String, Float>> all_tf){HashMap<String, Float> resIdf = new HashMap<String, Float>();HashMap<String, Integer> dict = new HashMap<String, Integer>();int docNum = FileList.size();for(int i = 0; i < docNum; i++){HashMap<String, Float> 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<String,HashMap<String, Float>> all_tf,HashMap<String, Float> idfs){HashMap<String, HashMap<String, Float>> resTfIdf = new HashMap<String, HashMap<String, Float>>();int docNum = FileList.size();for(int i = 0; i < docNum; i++){String filepath = FileList.get(i);HashMap<String, Float> tfidf = new HashMap<String, Float>();HashMap<String, Float> 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<String, HashMap<String, Float>> 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<String, Float> temp = (HashMap<String, Float>) 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 stubString file = "D:/testfiles";HashMap<String,HashMap<String, Float>> all_tf = tfAllFiles(file);System.out.println();HashMap<String, Float> idfs = idf(all_tf);System.out.println();tf_idf(all_tf, idfs);}}