基于贝叶斯的垃圾邮件过滤器 JAVA

<span style="font-size: 18px;">package cn.zhf.test;  

import java.io.*;  
import java.util.*;  

public class SpamMailDetection {  
    public static final String BASE_PATH = "C:\Users\zhf\Desktop\mail";  
    public static final String SPAM_PATH = BASE_PATH + "\train_illegal.txt";//垃圾邮件语料  
    public static final String OK_PATH = BASE_PATH + "\train_legal.txt";//正常邮件语料  
    public static final String EMAIL_PATH = BASE_PATH + "\to_judge.txt";//要判别的邮件  
    public static final String DICT_PATH = BASE_PATH + "\dict.txt";//分词用的词典  

    public static void main(String[] args) {  
        SpamMailDetection smc = new SpamMailDetection();  
        //<word,(word/NonSpamCorpus)>  
        Map<String, Double> okmap = smc.createMailMap(OK_PATH);  
        //<word,(word/SpamCorpus)>  
        Map<String, Double> spammap = smc.createMailMap(SPAM_PATH);  
        Map<String, Double> ratemap = smc.createSpamProbabilityMap(spammap, okmap);  
        double probability = smc.judgeMail(EMAIL_PATH, ratemap);  
        if (probability > 0.5)//概率大于0.5则判定为垃圾  
            System.out.println("It's an ok mail.");  
        else  
            System.out.println("It's a spam mail.");  

    }  

    /** 
     * 给定邮件,分词,根据分词结果判断是垃圾邮件的概率  
     * P(Spam|t1,t2,t3……tn)=（P1*P2*……PN）/(P1*P2*……PN+(1-P1)*(1-P2)*……(1-PN)) 
     */  
    public double judgeMail(String emailPath, Map<String, Double> ratemap) {  
        List<String> list = segment(readFile(emailPath));  
        double rate = 1.0;  
        double tempRate = 1.0;  
        for (String str : list) {  
            if (ratemap.containsKey(str)) {  
                double tmp = ratemap.get(str);  
                tempRate *= 1 - tmp;  
                rate *= tmp;  
            }  
        }  
        return rate / (rate + tempRate);  
    }  

    /** 
     * 从给定的垃圾邮件、正常邮件语料中建立map <切出来的词,出现的频率> 
     */  
    public Map<String, Double> createMailMap(String filePath) {  
        String str = readFile(filePath);  
        List<String> list = segment(str);  
        Map<String, Integer> tmpmap = new HashMap<String, Integer>();  
        Map<String, Double> retmap = new HashMap<String, Double>();  
        double rate = 0.0;  
        int count = 0;  
        for (String s : list) {  
            tmpmap.put(s, tmpmap.containsKey(s) ? count + 1 : 1);  
        }  
        for (Iterator iter = tmpmap.keySet().iterator(); iter.hasNext();) {  
            String key = (String) iter.next();  
            rate = tmpmap.get(key) / list.size();  
            retmap.put(key, rate);  
        }  
        return retmap;  
    }  

    /** 
     * 建立map,<str,rate> 邮件中出现ti时,该邮件为垃圾邮件的概率 
     * P( Spam|ti) =P2(ti )/((P1 (ti ) +P2 ( ti )) 
     */  
    public Map<String, Double> createSpamProbabilityMap(Map<String, Double> spammap,  
            Map<String, Double> okmap) {  
        Map<String, Double> retmap = new HashMap<String, Double>();  
        for (Iterator iter = spammap.keySet().iterator(); iter.hasNext();) {  
            String key = (String) iter.next();  
            double rate = spammap.get(key);  
            double allRate = rate;  
            if (okmap.containsKey(key)) {  
                allRate += okmap.get(key);  
            }  
            retmap.put(key, rate / allRate);  
        }  
        return retmap;  
    }  

    /** 
     * 中文分词 
     */  
    public List<String> segment(String str) {  
        Map<String, Integer> map = loadDict();  
        List<String> list = new ArrayList<String>();  
        int len = str.length();  
        String term;  
        int maxSize = 6;  
        int i = 0, j = 0;  
        while (i < len) {  
            int n = i + maxSize < len ? i + maxSize : len + 1;  
            boolean findFlag = false;  
            for (j = n - 1; j > i; j--) {  
                term = str.substring(i, j);  
                if (map.containsKey(term)) {  
                    list.add(term);  
                    findFlag = true;  
                    i = j;  
                    break;  
                }  
            }  
            if (findFlag == false)  
                i = j + 1;  
        }  
        return list;  
    }  

    /** 
     * 加载词典文件 
     */  
    public Map<String, Integer> loadDict() {  
        Map<String, Integer> map = new HashMap<String, Integer>();  
        String[] str;  
        try {  
            BufferedReader br = new BufferedReader(new InputStreamReader(  
                    new FileInputStream(new File(DICT_PATH)), "gbk"));  
            String tmp = "";  
            while ((tmp = br.readLine()) != null) {  
                str = tmp.split("	");  
                map.put(str[0], 0);  
            }  
            br.close();  
        } catch (FileNotFoundException e) {  
            e.printStackTrace();  
        } catch (IOException e) {  
            e.printStackTrace();  
        }  
        return map;  
    }  

    /** 
     * 读文件 
     */  
    public String readFile(String filePath) {  
        String str = "";  
        try {  
            BufferedReader br = new BufferedReader(new InputStreamReader(  
                    new FileInputStream(new File(filePath)), "gbk"));  
            String tmp = "";  
            while ((tmp = br.readLine()) != null)  
                str += tmp;  
            br.close();  
        } catch (FileNotFoundException e) {  
            e.printStackTrace();  
        } catch (IOException e) {  
            e.printStackTrace();  
        }  
        return str;  
    }  

}  
</span>