Android Open Source - smsAndCallFilter S K Spam Blocker

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The source code is released under:

/* * Author: Hasib Al Muhaimin. * * The contents of this file are subject to the Mozilla Public License * Version 1.1 (the "License"); you may not use this file except in * compliance with the L...

Java Source Code

/*
 * Author: Hasib Al Muhaimin./*from  w  w  w. ja v a  2 s .  c  o m*/
 * 
 * The contents of this file are subject to the Mozilla Public License
 * Version 1.1 (the "License"); you may not use this file except in
 * compliance with the License. You may obtain a copy of the License at
 * http://www.mozilla.org/MPL/
 * 
 */


package com.sadakhata.spamsmsblocker;

import com.sadakhata.ml.*;
import com.sadakhata.banglatoenglishrupantor.*;
import java.util.Locale;
import android.content.res.AssetManager;

 /**
  *These imports should not be
   *there when deploying. These imports
   *are only for training dataset.
**/
/*
import org.apache.poi.hssf.usermodel.HSSFCell;
import org.apache.poi.hssf.usermodel.HSSFRow;
import org.apache.poi.hssf.usermodel.HSSFSheet;
import org.apache.poi.hssf.usermodel.HSSFWorkbook;
*/

public class SKSpamBlocker{
  SKNeuralNetwork skneuralnetwork;
  int numInputUnit;
  int numOutputUnit;
  boolean initiated = false;


  //101 prime number
  double primes[] = {1, 1, 2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109, 113, 127, 131, 137, 139, 149, 151, 157, 163, 167, 173, 179, 181, 191, 193, 197, 199, 211, 223, 227, 229, 233, 239, 241, 251, 257, 263, 269, 271, 277, 281, 283, 293, 307, 311, 313, 317, 331, 337, 347, 349, 353, 359, 367, 373, 379, 383, 389, 397, 401, 409, 419, 421, 431, 433, 439, 443, 449, 457, 461, 463, 467, 479, 487, 491, 499, 503, 509, 521, 523};

  public void init(AssetManager assetmanager)
  {
    if(!initiated)
    {
      numInputUnit = 500;
      numOutputUnit = 2;

      skneuralnetwork = new SKNeuralNetwork(numInputUnit, numOutputUnit, 1, 10, "SPAMBLOCKER.dat", assetmanager );

      initiated = true;
    }

    //train("sms.xls", 0);
  }


  public boolean isSpam(String mobileNo, String msg)
  {
    boolean spam = false;
    char ch;
    int len = mobileNo.length();
    for(int i=0; i<len; i++)
    {
      ch = mobileNo.charAt(i);
      if( !( (ch == '+') || ('0' <= ch && ch <='9') ) )
      {
        spam = true;
        break;
      }
    }

    if(spam)
    {
      return true;
    }
    else
    {
      double x[] = new double[numInputUnit];
      hashFullString(x, msg);
      return (skneuralnetwork.feedForward( x ) == 1 );
    }
  }


  private void hashFullString(double x[], String msg)
  {
        msg = Rupantor.convert(msg);
    msg = msg.toLowerCase(Locale.ENGLISH);
    String delims = "[^a-z]+";
    String msgtokens[] = msg.split(delims);
    
    int h;


    /*
     | k
     |-----------------------------------------------------------
     | How many hash function we want to generate from one word.
     | This is a bloom Filter Idea.
     |------------------------------------------------------------
     */
    int k = 5;
    for(int i=0; i<msgtokens.length; i++)
    {
      for(int j=1; j<k; j++)
      {
        h = hash(msgtokens[i], (255.0*j)/(double)k);
        x[h] = Math.sqrt(x[h]) + 0.25;    
      }
    }
  }


  private int hash(String str, double reduce)
  {
    int len = Math.min(str.length(), 100);
  
    double sum = 0;

    for(int i=0; i<len; i++)
    {
      sum = sum + ( (str.charAt(i) - reduce)*primes[i] )/primes[i+1];
    }

    int ret = ((int)sum % numInputUnit);
    
    if(ret < 0) // precaution.
    {
      ret = ret + numInputUnit;
    }
    return ret;
  }

  /*
  private void train(String excelFileName, int times)
  {
    /*
     |-------------------------------------------------------------
     | Number of SMS in xls file.
     | set the initial value to zero. So that We can follow any 
     | error occured at reading number of sms dynamically.
     |-------------------------------------------------------------
     
    int numSms = 0; 
    try{
      /*
       |---------------------------------------------------------
       | getLastRowNum() return a zero based index of lastRow.
       |---------------------------------------------------------
       
      numSms = (new HSSFWorkbook(new FileInputStream(excelFileName)).getSheetAt(0)).getLastRowNum() + 1;
      System.out.println(numSms);
    }catch(Exception e)
    {
      e.printStackTrace();
    }

    double x[][] = new double[numSms][numInputUnit];
    double t[][] = new double[numSms][numOutputUnit];

    readExcelFile(excelFileName, x, t, numSms);
    
    for(int i=1; i<=times; i++)
    {
      System.out.print(i+".\t");
      skneuralnetwork.backPropagate(x, t, numSms);

      if((i%100) == 0)
      {
        skneuralnetwork.saveData();
      }
    }

    System.out.println("Total Trained: " + skneuralnetwork.getNumTrained() );
    skneuralnetwork.printCostFunctionJ(x, t, numSms);
    
    
    //checking how many classification error in the Training set.
    int totalError = 0;
    for(int i=0; i < numSms; i++)
    {
      if(t[i][ skneuralnetwork.feedForward(x[i]) ] == 0)
      {
        totalError++;
        System.out.println(i+" = "+skneuralnetwork.feedForward(x[i]));
      }
    }
    System.out.println("TotalError = " + totalError);
    

    

  }

  private void readExcelFile(String excelFileName, double x[][], double t[][], int numRows)
  {
    
    try{
      HSSFWorkbook workbook = new HSSFWorkbook(new FileInputStream(excelFileName));
      HSSFSheet worksheet = workbook.getSheetAt(0);
      for(int rowIdx = 0; rowIdx < numRows; rowIdx++ )
      {
        HSSFRow row = worksheet.getRow(rowIdx);

        String msgCellVal = row.getCell(4).getStringCellValue();
        int spamCellVal = (int)row.getCell(5).getNumericCellValue();

        hashFullString(x[rowIdx], msgCellVal);
        t[rowIdx][spamCellVal] = 1;

        //System.out.println(rowIdx);
      }
    
    }catch (FileNotFoundException e) {
      e.printStackTrace();
    } catch (IOException e) {
      e.printStackTrace();
    } catch(Exception e) {
      e.printStackTrace();
    }
    
  }
  */
}

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