/*
* To change this license header, choose License Headers in Project Properties.
* To change this template file, choose Tools | Templates
* and open the template in the editor.
*/
package freewill_project;
import java.util.Arrays;
import javax.swing.JOptionPane;
/**
*
* #author ///
*/
public class Testing {
public static void main(String[] args) {
int batas = Integer.parseInt(JOptionPane.showInputDialog("Batas Siswa"));
String[] nama = new String[batas];
String mapel1, mapel2;
int nilai1[] = new int[batas];
int nilai2[] = new int[batas];
int total1 = 0, total2 = 0, Ttotal;
int kkm1, kkm2, k=0;
String[] tlulus1 = new String[nama.length];
String[] lulus1 = new String[nama.length];
String[] tlulus2 = new String[nama.length];
String[] lulus2 = new String[nama.length];
int jumlah = 0;
mapel1 = JOptionPane.showInputDialog("Masukan Mapel 1");
mapel2 = JOptionPane.showInputDialog("Masukan Mapel 2");
kkm1 = (Integer.parseInt(JOptionPane.showInputDialog("Input KKM 1")));
kkm2 = (Integer.parseInt(JOptionPane.showInputDialog("Input KKM 2")));
for (int i = 0; i < nama.length; i++) {
nama[i] = (JOptionPane.showInputDialog("Nama Siswa"));
nilai1[i] = Integer.parseInt(JOptionPane.showInputDialog("Input Nilai"));
total1 += nilai1[i];
if (nilai1[i] < kkm1) {
tlulus1[i] = nama[i];
} else {
nama[i] = lulus1[i];
}
nilai2[i] = Integer.parseInt(JOptionPane.showInputDialog("Input Nilai"));
total2 += nilai2[i];
if (nilai2[i] < kkm2) {
nama[i] = tlulus2[i];
} else {
nama[i] = lulus2[i];
}
}
Ttotal = total1 + total2;
int rata = Ttotal / 2;
int max1 = nilai1[0];
int min1 = nilai1[0];
int max2 = nilai2[0];
int min2 = nilai2[0];
for (int i = 0; i < 2; i++) { //for untuk output max, min, jumlah, rata arrays
if (max1 < nilai1[i]) {
max1 = nilai1[i];
} else if (min1 > nilai1[i]) {
min1 = nilai1[i];
}
if (max2 < nilai2[i]) {
max2 = nilai2[i];
} else if (min2 > nilai2[i]) {
min2 = nilai2[i];
}
}
System.out.println("Nilai Rata: " + rata + "\nNilai Tertinggi1: " + max1 + "\nNilai Terendah1: " + min2 + "\nNilai Tertinggi2: " + max2 + "\nNilai Terendah2: " + min2 + "\nSiswa Lulus1: " + Arrays.toString(lulus1) + "\nSiswa Tidak Lulus1: " + Arrays.toString(tlulus1) + "\nSiswa Lulus2: " + Arrays.toString(lulus2) + "\nSiswa Tidak Lulus2: " + Arrays.toString(tlulus2));
}
}
if the nilai is less than the kkm, then an element of the array in nama will be copied to tlulus, else an element in nama will be copied to lulus, however the output shows both lulus and tlulus as null
the output of lulus and tlulus should contain elements of nama, it showed up as null instead, I tried several fixes but then I get Arrays.outofbounds exception, any solution?
Your code
} else {
nama[i] = lulus1[i];
}
does not seem to match your specification:
else an element in nama will be copied to lulus
Shouldn't it rather be
} else {
lulus1[i] = nama[i];
}
?
Your code can lead to nama inputs being overwritten with null.
I have such a big problem with implementation the svm_predict function. I have trained svm, and prepare datatest. Both files are in .txt. file.Datatest are from LBP( Local Binary patterns) and it looks like:
-0.6448744548418511
-0.7862774302452588
1.7746263060948377
I'm loading it to the svm_predict function and at my console after compiling my program there is:
Accuracy = 0.0% (0/800) (classification)
So it's look like it can't read datatest?
import libsvm.*;
import java.io.*;
import java.util.*;
class svm_predict {
private static double atof(String s)
{
return Double.valueOf(s).doubleValue();
}
private static int atoi(String s)
{
return Integer.parseInt(s);
}
private static void predict(BufferedReader input, DataOutputStream output, svm_model model, int predict_probability) throws IOException
{
int correct = 0;
int total = 0;
double error = 0;
double sumv = 0, sumy = 0, sumvv = 0, sumyy = 0, sumvy = 0;
int svm_type=svm.svm_get_svm_type(model);
int nr_class=svm.svm_get_nr_class(model);
double[] prob_estimates=null;
if(predict_probability == 1)
{
if(svm_type == svm_parameter.EPSILON_SVR ||
svm_type == svm_parameter.NU_SVR)
{
System.out.print("Prob. model for test data: target value = predicted value + z,\nz: Laplace distribution e^(-|z|/sigma)/(2sigma),sigma="+svm.svm_get_svr_probability(model)+"\n");
}
else
{
int[] labels=new int[nr_class];
svm.svm_get_labels(model,labels);
prob_estimates = new double[nr_class];
output.writeBytes("labels");
for(int j=0;j<nr_class;j++)
output.writeBytes(" "+labels[j]);
output.writeBytes("\n");
}
}
while(true)
{
String line = input.readLine();
if(line == null) break;
StringTokenizer st = new StringTokenizer(line," \t\n\r\f:");
double target = atof(st.nextToken());
int m = st.countTokens()/2;
svm_node[] x = new svm_node[m];
for(int j=0;j<m;j++)
{
x[j] = new svm_node();
x[j].index = atoi(st.nextToken());
x[j].value = atof(st.nextToken());
}
double v;
if (predict_probability==1 && (svm_type==svm_parameter.C_SVC || svm_type==svm_parameter.NU_SVC))
{
v = svm.svm_predict_probability(model,x,prob_estimates);
output.writeBytes(v+" ");
for(int j=0;j<nr_class;j++)
output.writeBytes(prob_estimates[j]+" ");
output.writeBytes("\n");
}
else
{
v = svm.svm_predict(model,x);
output.writeBytes(v+"\n");
}
if(v == target)
++correct;
error += (v-target)*(v-target);
sumv += v;
sumy += target;
sumvv += v*v;
sumyy += target*target;
sumvy += v*target;
++total;
}
if(svm_type == svm_parameter.EPSILON_SVR ||
svm_type == svm_parameter.NU_SVR)
{
System.out.print("Mean squared error = "+error/total+" (regression)\n");
System.out.print("Squared correlation coefficient = "+
((total*sumvy-sumv*sumy)*(total*sumvy-sumv*sumy))/
((total*sumvv-sumv*sumv)*(total*sumyy-sumy*sumy))+
" (regression)\n");
}
else
System.out.print("Accuracy = "+(double)correct/total*100+
"% ("+correct+"/"+total+") (classification)\n");
}
private static void exit_with_help()
{
System.err.print("usage: svm_predict [options] test_file model_file output_file\n"
+"options:\n"
+"-b probability_estimates: whether to predict probability estimates, 0 or 1 (default 0); one-class SVM not supported yet\n");
System.exit(1);
}
public static void main(String argv[]) throws IOException
{
int i, predict_probability=0;
// parse options
for(i=0;i<argv.length;i++)
{
if(argv[i].charAt(0) != '-') break;
++i;
switch(argv[i-1].charAt(1))
{
case 'b':
predict_probability = atoi(argv[i]);
break;
default:
System.err.print("Unknown option: " + argv[i-1] + "\n");
exit_with_help();
}
}
if(i>=argv.length-2)
exit_with_help();
try
{
BufferedReader input = new BufferedReader(new FileReader(argv[i]));
DataOutputStream output = new DataOutputStream(new BufferedOutputStream(new FileOutputStream(argv[i+2])));
svm_model model = svm.svm_load_model(argv[i+1]);
if(predict_probability == 1)
{
if(svm.svm_check_probability_model(model)==0)
{
System.err.print("Model does not support probabiliy estimates\n");
System.exit(1);
}
}
else
{
if(svm.svm_check_probability_model(model)!=0)
{
System.out.print("Model supports probability estimates, but disabled in prediction.\n");
}
}
predict(input,output,model,predict_probability);
input.close();
output.close();
}
catch(FileNotFoundException e)
{
exit_with_help();
}
catch(ArrayIndexOutOfBoundsException e)
{
exit_with_help();
}
}
}
It's difficult to know becasue its a big process
make sure you follow their classification guide
the data should be scaled it seems it goes above 1 right now
I've been trying to work on this problem for a while now but to no avail. When I run the code I get this error message: incompatible types: edu.duke.StorageResource cannot be converted to java.lang.String on line String geneList = FMG.storeAll(dna);. Does this mean I'm trying to make edu.duke object work with a java.lang.String type object? What would we go about resolving this issue?
Here's my code so far:
package coursera_java_duke;
import java.io.*;
import edu.duke.FileResource;
import edu.duke.StorageResource;
import edu.duke.DirectoryResource;
public class FindMultiGenes5 {
public int findStopIndex(String dna, int index) {
int stop1 = dna.indexOf("TGA", index);
if (stop1 == -1 || (stop1 - index) % 3 != 0) {
stop1 = dna.length();
}
int stop2 = dna.indexOf("TAA", index);
if (stop2 == -1 || (stop2 - index) % 3 != 0) {
stop2 = dna.length();
}
int stop3 = dna.indexOf("TAG", index);
if (stop3 == -1 || (stop3 - index) % 3 != 0) {
stop3 = dna.length();
}
return Math.min(stop1, Math.min(stop2, stop3));
}
public StorageResource storeAll(String dna) {
//CATGTAATAGATGAATGACTGATAGATATGCTTGTATGCTATGAAAATGTGAAATGACCCAdna = "CATGTAATAGATGAATGACTGATAGATATGCTTGTATGCTATGAAAATGTGAAATGACCCA";
String geneAL = new String();
String sequence = dna.toUpperCase();
StorageResource store = new StorageResource();
int index = 0;
while (true) {
index = sequence.indexOf("ATG", index);
if (index == -1)
break;
int stop = findStopIndex(sequence, index + 3);
if (stop != sequence.length()) {
String gene = dna.substring(index, stop + 3);
store.add(gene);
//index = sequence.substring(index, stop + 3).length();
index = stop + 3; // start at the end of the stop codon
}else{ index = index + 3;
}
}
return store;//System.out.println(sequence);
}
public void testStorageFinder() {
DirectoryResource dr = new DirectoryResource();
StorageResource dnaStore = new StorageResource();
for (File f : dr.selectedFiles()) {
FileResource fr = new FileResource(f);
String s = fr.asString();
dnaStore = storeAll(s);
printGenes(dnaStore);
}
System.out.println("size = " + dnaStore.size());
}
public String readStrFromFile(){
FileResource readFile = new FileResource();
String DNA = readFile.asString();
//System.out.println("DNA: " + DNA);
return DNA;
}//end readStrFromFile() method;
public float calCGRatio(String gene){
gene = gene.toUpperCase();
int len = gene.length();
int CGCount = 0;
for(int i=0; i<len; i++){
if(gene.charAt(i) == 'C' || gene.charAt(i) == 'G')
CGCount++;
}//end for loop
System.out.println("CGCount " + CGCount + " Length: " + len + " Ratio: " + (float)CGCount/len);
return (float)CGCount/len;
}//end of calCGRatio() method;
public void printGenes(StorageResource sr){
//create a FindMultiGenesFile object FMG
FindMultiGenes5 FMG = new FindMultiGenes5();
//read a DNA sequence from file
String dna = FMG.readStrFromFile();
String geneList = FMG.storeAll(dna);
//store all genes into a document
StorageResource dnaStore = new StorageResource();
System.out.println("\n There are " + geneList.size() + " genes. ");
int longerthan60 = 0;
int CGGreaterthan35 = 0;
for(int i=0; i<geneList.size(); i++){
if(!dnaStore.contains(geneList.get(i)))
dnaStore.add(geneList.get(i));
if(geneList.get(i).length() > 60) longerthan60++;
if(FMG.calCGRatio(geneList.get(i)) > 0.35) CGGreaterthan35++;
}
System.out.println("dnaStore.size: " + dnaStore.size());
System.out.println("\n There are " + dnaStore.size() + " genes. ");
System.out.println("There are " + longerthan60 + " genes longer than 60.");
System.out.println("There are " + CGGreaterthan35 + " genes with CG ratio greater than 0.35.");
}//end main();
}
I found your post as I am also doing a similar course at Duke using those edu.duke libraries.
When I get that error message it is because I'm using the wrong method to access it.
Try FMD.data() to get an iterable of all of the gene strings.
Hi i found some code after do some Google and i am using this code to Encrypt the string (witch i set as parameter in web-service)
and it's working fine, it's to hard for me to understand this code so put hole class.
public class RSA {
Vector<Object> vectEnc;
Object enc[];
private long P, Q;
private long N, M, E = 11;
private long D;
public RSA() {
P = 6151;
Q = 8807;
N = P * Q;
M = (P - 1) * (Q - 1);
E = 11;
D = 44310191;
vectEnc = new Vector<Object>();
}
public String doEncryption(String message) {
try {
String str = new BASE64Encoder().encode(message.getBytes("UTF-8"));
String encString = "";
for (int i = 0; i < str.length(); i += 3) {
String tempAsci = "1";
String tempStr;
for (int h = 0; h < 3; h++) {
int total = i + h;
if (total < str.length()) {
tempStr = String.valueOf((int) (str.subSequence(total,
total + 1).charAt(0)) - 30);
if (tempStr.length() < 2) {
tempStr = "0" + tempStr;
}
} else {
break;
}
tempAsci = tempAsci + tempStr;
}
vectEnc.add(tempAsci + "1");
}
enc = vectEnc.toArray();
vectEnc.removeAllElements();
for (int i = 0; i < enc.length; i++) {
long base = Long.parseLong(enc[i].toString());
long powMod = powMod(base, E, N);
encString = encString + String.valueOf(powMod) + " ";
}
return encString;
} catch (Exception e) {
e.printStackTrace();
return null;
}
}
public String doDecryption(String codeMsg) {
String[] decryptArray = codeMsg.split(" ");
String decryptStr = "";
String originalStr = "";
for (int i = 0; i < decryptArray.length; i++) {
long base = Long.parseLong(decryptArray[i]);
long powMod = powMod(base, D, N);
String powModString = String.valueOf(powMod);
decryptStr = decryptStr
+ powModString.subSequence(1, powModString.length() - 1);
}
for (int i = 0; i < decryptStr.length(); i += 2) {
char ch = (char) (Integer.parseInt(decryptStr.subSequence(i, i + 2)
.toString()) + 30);
originalStr = originalStr + ch;
}
BASE64Decoder decoder = new BASE64Decoder();
byte[] decBytes = null;
try {
decBytes = decoder.decodeBuffer(originalStr);
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
String decodeStr = new String(decBytes);
return decodeStr;
}
public long powMod(long base, long exp, long modula) {
long accum = 1;
int i = 0;
long base2 = base;
while ((exp >> i) > 0) {
if (((exp >> i) & 1) == 1) {
accum = mo((accum * base2), modula);
}
base2 = mo((base2 * base2), modula);
i++;
}
return accum;
}
public long mo(long g, long l) {
return (long) (g - (l * Math.floor(g / l)));
}
}
But the problem is when the String Length is more the 56 it throw the Exception Like
java.lang.NumberFormatException: For input string: "174-17-201"
at java.lang.NumberFormatException.forInputString(Unknown Source)
at java.lang.Long.parseLong(Unknown Source)
at java.lang.Long.parseLong(Unknown Source)
at com.info.test.RSA.doEncryption(RSA.java:49)
at com.info.test.Test.main(Test.java:56)
i even no what is the algorithm is use by this code ,i do some Google and i found simple solution is make a part of string and do Encryption it Like this.
int MAX_LAN = 55;
List<String> splitEqually = splitEqually(string,MAX_LAN);
String encodeString = "";
for (int i = 0; i < splitEqually.size(); i++) {
encodeString +=rsa.doEncryption(splitEqually.get(i));
}
System.out.println(encodeString);
public static List<String> splitEqually(String text, int size) {
List<String> ret = new ArrayList<String>((text.length() + size - 1) / size);
for (int start = 0; start < text.length(); start += size) {
ret.add(text.substring(start, Math.min(text.length(), start + size)));
}
return ret;
}
and it working fine , so is it proper method or not ??
I would strongly suggest using Java's built-in cryptographic libraries for this. Follow this series of articles on how to perform RSA encryption/decryption in Java:
http://www.javamex.com/tutorials/cryptography/rsa_encryption.shtml
I used lingpipe for sentence detection but I don't have any idea if there is a better tool. As far as I have understood, there is no way to compare two sentences and see if they mean the same thing.
Is there anyother good source where I can have a pre-built method for comparing two sentences and see if they are similar?
My requirement is as below:
String sent1 = "Mary and Meera are my classmates.";
String sent2 = "Meera and Mary are my classmates.";
String sent3 = "I am in Meera and Mary's class.";
// several sentences will be formed and basically what I need to do is
// this
boolean bothAreEqual = compareOf(sent1, sent2);
sop(bothAreEqual); // should print true
boolean bothAreEqual = compareOf(sent2, sent3);
sop(bothAreEqual);// should print true
How to test if the meaning of two sentences are the same: this would be a too open-ended question.
However, there are methods for comparing two sentences and see if they are similar. There are many possible definition for similarity that can be tested with pre-built methods.
See for example http://en.wikipedia.org/wiki/Levenshtein_distance
Distance between
'Mary and Meera are my classmates.'
and 'Meera and Mary are my classmates.':
6
Distance between
'Mary and Meera are my classmates.'
and 'Alice and Bobe are not my classmates.':
14
Distance between
'Mary and Meera are my classmates.'
and 'Some totally different sentence.':
29
code:
public class LevenshteinDistance {
private static int minimum(int a, int b, int c) {
return Math.min(Math.min(a, b), c);
}
public static int computeDistance(CharSequence str1,
CharSequence str2) {
int[][] distance = new int[str1.length() + 1][str2.length() + 1];
for (int i = 0; i <= str1.length(); i++){
distance[i][0] = i;
}
for (int j = 0; j <= str2.length(); j++){
distance[0][j] = j;
}
for (int i = 1; i <= str1.length(); i++){
for (int j = 1; j <= str2.length(); j++){
distance[i][j] = minimum(
distance[i - 1][j] + 1,
distance[i][j - 1] + 1,
distance[i - 1][j - 1]
+ ((str1.charAt(i - 1) == str2.charAt(j - 1)) ? 0 : 1));
}
}
int result = distance[str1.length()][str2.length()];
//log.debug("distance:"+result);
return result;
}
public static void main(String[] args) {
String sent1="Mary and Meera are my classmates.";
String sent2="Meera and Mary are my classmates.";
String sent3="Alice and Bobe are not my classmates.";
String sent4="Some totally different sentence.";
System.out.println("Distance between \n'"+sent1+"' \nand '"+sent2+"': \n"+computeDistance(sent1, sent2));
System.out.println("Distance between \n'"+sent1+"' \nand '"+sent3+"': \n"+computeDistance(sent1, sent3));
System.out.println("Distance between \n'"+sent1+"' \nand '"+sent4+"': \n"+computeDistance(sent1, sent4));
}
}
Here is wat i have come up with. this is just a substitute till i get to the real thing but it might be of some help to people out there..
package com.examples;
import java.io.File;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import com.aliasi.sentences.MedlineSentenceModel;
import com.aliasi.sentences.SentenceModel;
import com.aliasi.tokenizer.IndoEuropeanTokenizerFactory;
import com.aliasi.tokenizer.Tokenizer;
import com.aliasi.tokenizer.TokenizerFactory;
import com.aliasi.util.Files;
import com.sun.accessibility.internal.resources.accessibility;
public class SentenceWordAnalysisAndLevenshteinDistance {
private static int minimum(int a, int b, int c) {
return Math.min(Math.min(a, b), c);
}
public static int computeDistance(CharSequence str1, CharSequence str2) {
int[][] distance = new int[str1.length() + 1][str2.length() + 1];
for (int i = 0; i <= str1.length(); i++) {
distance[i][0] = i;
}
for (int j = 0; j <= str2.length(); j++) {
distance[0][j] = j;
}
for (int i = 1; i <= str1.length(); i++) {
for (int j = 1; j <= str2.length(); j++) {
distance[i][j] = minimum(
distance[i - 1][j] + 1,
distance[i][j - 1] + 1,
distance[i - 1][j - 1]
+ ((str1.charAt(i - 1) == str2.charAt(j - 1)) ? 0
: 1));
}
}
int result = distance[str1.length()][str2.length()];
return result;
}
static final TokenizerFactory TOKENIZER_FACTORY = IndoEuropeanTokenizerFactory.INSTANCE;
static final SentenceModel SENTENCE_MODEL = new MedlineSentenceModel();
public static void main(String[] args) {
try {
ArrayList<String> sentences = null;
sentences = new ArrayList<String>();
// Reading from text file
// sentences = readSentencesInFile("D:\\sam.txt");
// Giving sentences
// ArrayList<String> sentences = new ArrayList<String>();
sentences.add("Mary and Meera are my classmates.");
sentences.add("Mary and Meera are my classmates.");
sentences.add("Meera and Mary are my classmates.");
sentences.add("Alice and Bobe are not my classmates.");
sentences.add("Some totally different sentence.");
// Self-implemented
wordAnalyser(sentences);
// Internet referred
// levenshteinDistance(sentences);
} catch (Exception e) {
// TODO: handle exception
e.printStackTrace();
}
}
private static ArrayList<String> readSentencesInFile(String path) {
ArrayList<String> sentencesList = new ArrayList<String>();
try {
System.out.println("Reading file from : " + path);
File file = new File(path);
String text = Files.readFromFile(file, "ISO-8859-1");
System.out.println("INPUT TEXT: ");
System.out.println(text);
List<String> tokenList = new ArrayList<String>();
List<String> whiteList = new ArrayList<String>();
Tokenizer tokenizer = TOKENIZER_FACTORY.tokenizer(
text.toCharArray(), 0, text.length());
tokenizer.tokenize(tokenList, whiteList);
System.out.println(tokenList.size() + " TOKENS");
System.out.println(whiteList.size() + " WHITESPACES");
String[] tokens = new String[tokenList.size()];
String[] whites = new String[whiteList.size()];
tokenList.toArray(tokens);
whiteList.toArray(whites);
int[] sentenceBoundaries = SENTENCE_MODEL.boundaryIndices(tokens,
whites);
System.out.println(sentenceBoundaries.length
+ " SENTENCE END TOKEN OFFSETS");
if (sentenceBoundaries.length < 1) {
System.out.println("No sentence boundaries found.");
return new ArrayList<String>();
}
int sentStartTok = 0;
int sentEndTok = 0;
for (int i = 0; i < sentenceBoundaries.length; ++i) {
sentEndTok = sentenceBoundaries[i];
System.out.println("SENTENCE " + (i + 1) + ": ");
StringBuffer sentenceString = new StringBuffer();
for (int j = sentStartTok; j <= sentEndTok; j++) {
sentenceString.append(tokens[j] + whites[j + 1]);
}
System.out.println(sentenceString.toString());
sentencesList.add(sentenceString.toString());
sentStartTok = sentEndTok + 1;
}
} catch (IOException e) {
// TODO: handle exception
e.printStackTrace();
}
return sentencesList;
}
private static void levenshteinDistance(ArrayList<String> sentences) {
System.out.println("\nLevenshteinDistance");
for (int i = 0; i < sentences.size(); i++) {
System.out.println("Distance between \n'" + sentences.get(0)
+ "' \nand '" + sentences.get(i) + "': \n"
+ computeDistance(sentences.get(0),
sentences.get(i)));
}
}
private static void wordAnalyser(ArrayList<String> sentences) {
System.out.println("No.of Sentences : " + sentences.size());
List<String> stopWordsList = getStopWords();
List<String> tokenList = new ArrayList<String>();
ArrayList<List<String>> filteredSentences = new ArrayList<List<String>>();
for (int i = 0; i < sentences.size(); i++) {
tokenList = new ArrayList<String>();
List<String> whiteList = new ArrayList<String>();
Tokenizer tokenizer = TOKENIZER_FACTORY.tokenizer(sentences.get(i)
.toCharArray(), 0, sentences.get(i).length());
tokenizer.tokenize(tokenList, whiteList);
System.out.print("Sentence " + (i + 1) + ": " + tokenList.size()
+ " TOKENS, ");
System.out.println(whiteList.size() + " WHITESPACES");
filteredSentences.add(filterStopWords(tokenList, stopWordsList));
}
for (int i = 0; i < sentences.size(); i++) {
System.out.println("\n" + (i + 1) + ". Comparing\n '"
+ sentences.get(0) + "' \nwith\n '" +
sentences.get(i)
+ "' : \n");
System.out.println(filteredSentences.get(0) + "\n and \n"
+ filteredSentences.get(i));
System.out.println("Percentage of similarity: "
+ calculateSimilarity(filteredSentences.get(0),
filteredSentences.get(i))
+ "%");
}
}
private static double calculateSimilarity(List<String> list1,
List<String> list2) {
int length1 = list1.size();
int length2 = list2.size();
int count1 = 0;
int count2 = 0;
double result1 = 0.0;
double result2 = 0.0;
int least, highest;
if (length2 > length1) {
least = length1;
highest = length2;
} else {
least = length2;
highest = length1;
}
// computing result1
for (String string1 : list1) {
if (list2.contains(string1))
count1++;
}
result1 = (count1 * 100) / length1;
// computing result2
for (String string2 : list2) {
if (list1.contains(string2))
count2++;
}
result2 = (count2 * 100) / length2;
double avg = (result1 + result2) / 2;
return avg;
}
private static List<String> getStopWords() {
String stopWordsString = ".,a,able,about,across,after,all,almost,also,am,among,an,and,any,are,as,at,be,because,been,but,by,can,cannot,could,dear,did,do,does,either,else,ever,every,for,from,get,got,had,has,have,he,her,hers,him,his,how,however,i,if,in,into,is,it,its,just,least,let,like,likely,may,me,might,most,must,my,neither,no,nor,not,of,off,often,on,only,or,other,our,own,rather,said,say,says,she,should,since,so,some,than,that,the,their,them,then,there,these,they,this,tis,to,too,twas,us,wants,was,we,were,what,when,where,which,while,who,whom,why,will,with,would,yet,you,your";
List<String> stopWordsList = new ArrayList<String>();
List<String> stopWordTokenList = new ArrayList<String>();
List<String> whiteList = new ArrayList<String>();
Tokenizer tokenizer = TOKENIZER_FACTORY.tokenizer(
stopWordsString.toCharArray(), 0, stopWordsString.length());
tokenizer.tokenize(stopWordTokenList, whiteList);
for (int i = 0; i < stopWordTokenList.size(); i++) {
// System.out.println((i + 1) + ":" + tokenList.get(i));
if (!stopWordTokenList.get(i).equals(",")) {
stopWordsList.add(stopWordTokenList.get(i));
}
}
System.out.println("No.of stop words: " + stopWordsList.size());
return stopWordsList;
}
private static List<String> filterStopWords(List<String> tokenList,
List<String> stopWordsList) {
List<String> filteredSentenceWords = new ArrayList<String>();
for (String sentenceToken : tokenList) {
if (!stopWordsList.contains(sentenceToken)) {
filteredSentenceWords.add(sentenceToken);
}
}
return filteredSentenceWords;
}
}