TFIDF算法java实现

一、算法简介

        TF-IDF（term frequency–inverse document frequency）。

        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t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，IDF越大，则说明词条t具有很好的类别区分能力。

二、算法实现

1》主要文件

package tfidf; import java.io.BufferedReader; import java.io.File; import java.io.FileInputStream; import java.io.FileNotFoundException; import java.io.IOException; import java.io.InputStreamReader; import java.io.UnsupportedEncodingException; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; import jeasy.analysis.MMAnalyzer; public class ReadFiles {     private static List<String> fileList = new ArrayList<String>();     private static HashMap<String, HashMap<String, Float>> allTheTf = new HashMap<String, HashMap<String, Float>>();     private static HashMap<String, HashMap<String, Integer>> allTheNormalTF = new HashMap<String, HashMap<String, Integer>>();     public static List<String> readDirs(String filepath) throws FileNotFoundException, IOException {         try {             File file = new File(filepath);             if (!file.isDirectory()) {                 System.out.println("输入的参数应该为[文件夹名]");                 System.out.println("filepath: " + file.getAbsolutePath());             } else if (file.isDirectory()) {                 String[] filelist = file.list();                 for (int i = 0; i < filelist.length; i++) {                     File readfile = new File(filepath + "\\" + filelist[i]);                     if (!readfile.isDirectory()) {                         //System.out.println("filepath: " + readfile.getAbsolutePath());                         fileList.add(readfile.getAbsolutePath());                     } else if (readfile.isDirectory()) {                         readDirs(filepath + "\\" + filelist[i]);                     }                 }             }         } catch (FileNotFoundException e) {             System.out.println(e.getMessage());         }         return fileList;     }     public static String readFiles(String file) throws FileNotFoundException, IOException {         StringBuffer sb = new StringBuffer();         InputStreamReader is = new InputStreamReader(new FileInputStream(file), "gbk");         BufferedReader br = new BufferedReader(is);         String line = br.readLine();         while (line != null) {             sb.append(line).append("\r\n");             line = br.readLine();         }         br.close();         return sb.toString();     }     public static String[] cutWord(String file) throws IOException {         String[] cutWordResult = null;         String text = ReadFiles.readFiles(file);         MMAnalyzer analyzer = new MMAnalyzer();         //System.out.println("file content: "+text);         //System.out.println("cutWordResult: "+analyzer.segment(text, " "));         String tempCutWordResult = analyzer.segment(text, " ");         cutWordResult = tempCutWordResult.split(" ");         return cutWordResult;     }     public static HashMap<String, Float> tf(String[] cutWordResult) {         HashMap<String, Float> tf = new HashMap<String, Float>();//正规化         int wordNum = cutWordResult.length;         int wordtf = 0;         for (int i = 0; i < wordNum; i++) {             wordtf = 0;             for (int j = 0; j < wordNum; j++) {                 if (cutWordResult[i] != " " && i != j) {                     if (cutWordResult[i].equals(cutWordResult[j])) {                         cutWordResult[j] = " ";                         wordtf++;                     }                 }             }             if (cutWordResult[i] != " ") {                 tf.put(cutWordResult[i], (new Float(++wordtf)) / wordNum);                 cutWordResult[i] = " ";             }         }         return tf;     }     public static HashMap<String, Integer> normalTF(String[] cutWordResult) {         HashMap<String, Integer> tfNormal = new HashMap<String, Integer>();//没有正规化         int wordNum = cutWordResult.length;         int wordtf = 0;         for (int i = 0; i < wordNum; i++) {             wordtf = 0;             if (cutWordResult[i] != " ") {                 for (int j = 0; j < wordNum; j++) {                     if (i != j) {                         if (cutWordResult[i].equals(cutWordResult[j])) {                             cutWordResult[j] = " ";                             wordtf++;                         }                     }                 }                 tfNormal.put(cutWordResult[i], ++wordtf);                 cutWordResult[i] = " ";             }         }         return tfNormal;     }     public static Map<String, HashMap<String, Float>> tfOfAll(String dir) throws IOException {         List<String> fileList = ReadFiles.readDirs(dir);         for (String file : fileList) {             HashMap<String, Float> dict = new HashMap<String, Float>();             dict = ReadFiles.tf(ReadFiles.cutWord(file));             allTheTf.put(file, dict);         }         return allTheTf;     }     public static Map<String, HashMap<String, Integer>> NormalTFOfAll(String dir) throws IOException {         List<String> fileList = ReadFiles.readDirs(dir);         for (int i = 0; i < fileList.size(); i++) {             HashMap<String, Integer> dict = new HashMap<String, Integer>();             dict = ReadFiles.normalTF(ReadFiles.cutWord(fileList.get(i)));             allTheNormalTF.put(fileList.get(i), dict);         }         return allTheNormalTF;     }     public static Map<String, Float> idf(String dir) throws FileNotFoundException, UnsupportedEncodingException, IOException {         //公式IDF＝log((1+|D|)/|Dt|)，其中|D|表示文档总数，|Dt|表示包含关键词t的文档数量。         Map<String, Float> idf = new HashMap<String, Float>();         List<String> located = new ArrayList<String>();         float Dt = 1;         float D = allTheNormalTF.size();//文档总数         List<String> key = fileList;//存储各个文档名的List         Map<String, HashMap<String, Integer>> tfInIdf = allTheNormalTF;//存储各个文档tf的Map         for (int i = 0; i < D; i++) {             HashMap<String, Integer> temp = tfInIdf.get(key.get(i));             for (String word : temp.keySet()) {                 Dt = 1;                 if (!(located.contains(word))) {                     for (int k = 0; k < D; k++) {                         if (k != i) {                             HashMap<String, Integer> temp2 = tfInIdf.get(key.get(k));                             if (temp2.keySet().contains(word)) {                                 located.add(word);                                 Dt = Dt + 1;                                 continue;                             }                         }                     }                     idf.put(word, Log.log((1 + D) / Dt, 10));                 }             }         }         return idf;     }     public static Map<String, HashMap<String, Float>> tfidf(String dir) throws IOException {         Map<String, Float> idf = ReadFiles.idf(dir);         Map<String, HashMap<String, Float>> tf = ReadFiles.tfOfAll(dir);         for (String file : tf.keySet()) {             Map<String, Float> singelFile = tf.get(file);             for (String word : singelFile.keySet()) {                 singelFile.put(word, (idf.get(word)) * singelFile.get(word));             }         }         return tf;     } }

 2》辅助工具类

package tfidf; public class Log {     public static float log(float value, float base) {         return (float) (Math.log(value) / Math.log(base));     } }

3》测试类

package tfidf; import java.io.IOException; import java.util.HashMap; import java.util.Map; public class Main {     public static void main(String[] args) throws IOException {         Map<String, HashMap<String, Integer>> normal = ReadFiles.NormalTFOfAll("d:/dir");         for (String filename : normal.keySet()) {             System.out.println("fileName " + filename);             System.out.println("TF " + normal.get(filename).toString());         }         System.out.println("-----------------------------------------");         Map<String, HashMap<String, Float>> notNarmal = ReadFiles.tfOfAll("d:/dir");         for (String filename : notNarmal.keySet()) {             System.out.println("fileName " + filename);             System.out.println("TF " + notNarmal.get(filename).toString());         }         System.out.println("-----------------------------------------");         Map<String, Float> idf = ReadFiles.idf("d;/dir");         for (String word : idf.keySet()) {             System.out.println("keyword :" + word + " idf: " + idf.get(word));         }         System.out.println("-----------------------------------------");         Map<String, HashMap<String, Float>> tfidf = ReadFiles.tfidf("d:/dir");         for (String filename : tfidf.keySet()) {             System.out.println("fileName " + filename);             System.out.println(tfidf.get(filename));         }     } }

 
三、实验数据



四、实验结果



  五、项目所需依赖



 
 jar包下载地址：http://lvxiaolin1118.download.csdn.net/
注意jar包的版本，否则出现以下问题，请跟换如图版本的jar包。

六、常见疑问截图
1》没有加入lucene jar包



 2》加入的lucene jar包版本与je分词jar包不对应



 3》我自己又重新跑了一遍程序，正确的输入结果如下



 

   转自：http://xwrwc.blog.163.com/blog/static/46320003201010634132451/