Examples of dkpro.similarity.algorithms.api.TextSimilarityMeasure

dkpro.similarity.algorithms.api.TextSimilarityMeasure

    // These are the two input documents
    String[] tokens1 = "The quick brown fox jumps over the lazy dog".split(" ");     
    String[] tokens2 = "The quick brown dog jumps over the lazy fox".split(" ");
    
    // Compute a trigram relatedness    
    TextSimilarityMeasure measure = new WordNGramContainmentMeasure(3);


    double score = measure.getSimilarity(tokens1, tokens2);


    System.out.println("Trigram similarity: " + score);
    
    // Compute ESA relatedness on Wiktionary     
    /*VectorComparator esa = new VectorComparator(

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        String text2 = "This is a second different test .";


        List<String> tokens1 = Arrays.asList(text1.split(" "));
        List<String> tokens2 = Arrays.asList(text2.split(" "));
        
        TextSimilarityMeasure measure = new HultigSumoComparator();
        assertEquals(1.0, measure.getSimilarity(tokens1, tokens1), 0.000001);
        assertEquals(0.75729, measure.getSimilarity(tokens1, tokens2), 0.00001);
    }

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      throws IOException, SimilarityException
  {
    String[] text1 = "This is a test .".split(" ");
    String[] text2 = "This is an example .".split(" ");
  
    TextSimilarityMeasure lsa = new LsaSimilarityMeasure(new File("src/test/resources/model/test.sspace"));
    
    assertEquals(1.0, lsa.getSimilarity(text1, text1), 0.00001);
    assertEquals(0.837171, lsa.getSimilarity(text1, text2), 0.00001);


  }

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Related Classes of dkpro.similarity.algorithms.api.TextSimilarityMeasure

dkpro.similarity.example.WithoutDKPro

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