如何解决在Web API中获得的值与通过ws4j中的源代码

How to resolve the difference between the values attained in the Web API and the ones attained through the source in ws4j?(如何解决在Web API中获得的值与通过ws4j中的源代码获得的值之间的差异？)

问题描述

我使用ws4j库开发了以下用于句子语义匹配的API。但我没能得到语义上的相似之处。 输出以图像的形式附加，其中显示冗余或0的值。 是否有遗漏调用的库？

package ws4jv01;

import edu.cmu.lti.lexical_db.ILexicalDatabase;
import edu.cmu.lti.lexical_db.NictWordNet;
import edu.cmu.lti.ws4j.RelatednessCalculator;
import edu.cmu.lti.ws4j.impl.HirstStOnge;
import edu.cmu.lti.ws4j.impl.JiangConrath;
import edu.cmu.lti.ws4j.impl.LeacockChodorow;
import edu.cmu.lti.ws4j.impl.Lesk;
import edu.cmu.lti.ws4j.impl.Lin;
import edu.cmu.lti.ws4j.impl.Path;
import edu.cmu.lti.ws4j.impl.Resnik;
import edu.cmu.lti.ws4j.impl.WuPalmer;

public class SentenceMatcherSimilarityMatrix
{
 private static ILexicalDatabase db = new NictWordNet();
 public double[][] getSimilarityMatrix( String[] words1, String[] words2, RelatednessCalculator rc )
{
    double[][] result = new double[words1.length][words2.length];
    for ( int i=0; i<words1.length; i++ ){
        for ( int j=0; j<words2.length; j++ ) {
            double score = rc.calcRelatednessOfWords(words1[i], words2[j]);
            result[i][j] = score;
          }
        }
    return result;
  }
  private void compute (String[] words1, String[] words2)
  {
    System.out.println("WuPalmer");
    RelatednessCalculator rc1 = new WuPalmer(db);
       {
        double[][] s1 = getSimilarityMatrix(words1, words2,rc1);
        for(int i=0; i<words1.length; i++){
            for(int j=0; j< words2.length; j++){
                System.out.print(s1[i][j] +"	");
            } 
            System.out.println();
        }}
    System.out.println();
    System.out.println();

    System.out.println("Resnik");
    RelatednessCalculator rc2 = new Resnik(db);
    {
        double[][] s2 = getSimilarityMatrix(words1, words2,rc2);
        for(int i=0; i<words1.length; i++){
            for(int j=0; j< words2.length; j++){
                System.out.print(s2[i][j] +"	");
            } 
            System.out.println();
        }}
    System.out.println();
    System.out.println();

    System.out.println("JiangConrath");
    RelatednessCalculator rc3 = new JiangConrath(db);
    {
        double[][] s2 = getSimilarityMatrix(words1, words2,rc3);
        for(int i=0; i<words1.length; i++){
            for(int j=0; j< words2.length; j++){
                System.out.print(s2[i][j] +"	");
            } 
            System.out.println();
        }}
    System.out.println();
    System.out.println();

    System.out.println("Lin");
    RelatednessCalculator rc4 = new Lin(db);
    {
        double[][] s2 = getSimilarityMatrix(words1, words2,rc4);
        for(int i=0; i<words1.length; i++){
            for(int j=0; j< words2.length; j++){
                System.out.print(s2[i][j] +"	");
            } 
            System.out.println();
        }}
    System.out.println();
    System.out.println();

    System.out.println("LeacockChodrow");
    RelatednessCalculator rc5 = new LeacockChodorow(db);
    {
        double[][] s2 = getSimilarityMatrix(words1, words2,rc5);
        for(int i=0; i<words1.length; i++){
            for(int j=0; j< words2.length; j++){
                System.out.print(s2[i][j] +"	");
            } 
            System.out.println();
        }}
    System.out.println();
    System.out.println();

    System.out.println("Path");
    RelatednessCalculator rc6 = new Path(db);
    {
        double[][] s2 = getSimilarityMatrix(words1, words2,rc6);
        for(int i=0; i<words1.length; i++){
            for(int j=0; j< words2.length; j++){
                System.out.print(s2[i][j] +"	");
            } 
            System.out.println();
        }}
    System.out.println();
    System.out.println();

    System.out.println("Lesk");
    RelatednessCalculator rc7 = new Lesk(db);
    {
        double[][] s2 = getSimilarityMatrix(words1, words2,rc7);
        for(int i=0; i<words1.length; i++){
            for(int j=0; j< words2.length; j++){
                System.out.print(s2[i][j] +"	");
            } 
            System.out.println();
        }}
    System.out.println();
    System.out.println();

    System.out.println("HirstStOnge");
    RelatednessCalculator rc8 = new HirstStOnge(db);
    {
        double[][] s2 = getSimilarityMatrix(words1, words2,rc8);

        for(int i=0; i<words1.length; i++){
            for(int j=0; j< words2.length; j++){
                System.out.print(s2[i][j] +"	");
            } 
            System.out.println();
           }}
          }

public static void main(String[] args) 
{
    String sent1 = "The boy is playing with a dog.";
    String sent2 = "The kid is playing with his pet.";

    String[] words1 = sent1.split(" ");
    String[] words2 = sent2.split(" ");
    SentenceMatcherSimilarityMatrix sm1 = new SentenceMatcherSimilarityMatrix(); 
    sm1.compute(words1, words2);
}
}

Result set

推荐答案

相似性矩阵呈现中的细微优化：

for (int i = 0; i <= words1.length; i++) {
    for (int j = 0; j <= words2.length; j++) {
        if(i==0 && j==0) {
            System.out.print(" " + "	"); 
        } else if(i==0) {
            System.out.print(words2[j-1] + "	");
        } else if(j==0) {
            System.out.print(words1[i-1] + "	");
        } else {
            System.out.print(s1[i-1][j-1] + "	");
        }
    }
    System.out.println();
}

这将使矩阵显示为：

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