Example usage for weka.core.stemmers SnowballStemmer SnowballStemmer

Introduction

In this page you can find the example usage for weka.core.stemmers SnowballStemmer SnowballStemmer.

Prototype

public SnowballStemmer() 

Source Link

Document

initializes the stemmer ("porter").

Usage

From source file:graph.clustering.NodeClusterer.java

License:Apache License

private Instances preprocessNodesInfoInstances(Instances clusterTrainingSet) {
    String[] filterOptions = new String[10];
    filterOptions[0] = "-R"; // attribute indices
    filterOptions[1] = "first-last";
    filterOptions[2] = "-W"; // The number of words (per class if there is a
    // class attribute assigned) to attempt to
    // keep.//from   ww  w .  ja v a 2 s . com
    filterOptions[3] = "1000";
    filterOptions[4] = "-prune-rate"; // periodical pruning
    filterOptions[5] = "-1.0";
    filterOptions[6] = "-N"; // 0=not normalize
    filterOptions[7] = "0";
    filterOptions[8] = "-M"; // The minimum term frequency
    filterOptions[9] = "1";

    SnowballStemmer stemmer = new SnowballStemmer();
    stemmer.setStemmer("english");
    WordTokenizer tokenizer = new WordTokenizer();

    StringToWordVector s2wFilterer = new StringToWordVector();
    try {
        s2wFilterer.setOptions(filterOptions);
        s2wFilterer.setStemmer(stemmer);
        s2wFilterer.setTokenizer(tokenizer);
        s2wFilterer.setInputFormat(clusterTrainingSet);
        clusterTrainingSet = Filter.useFilter(clusterTrainingSet, s2wFilterer);
    } catch (Exception e1) {
        System.out.println("Error in converting string into word vectors:");
        e1.printStackTrace();
    }

    RemoveUseless ruFilter = new RemoveUseless();
    try {
        ruFilter.setInputFormat(clusterTrainingSet);
        clusterTrainingSet = Filter.useFilter(clusterTrainingSet, ruFilter);
    } catch (Exception e1) {
        System.out.println("Error in removing useless terms:");
        e1.printStackTrace();
    }

    return clusterTrainingSet;
}

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From source file:sumblr.Preprocessor.java

public Preprocessor() {
    this.stopwords = new Stopwords();
    this.stemmer = new SnowballStemmer();

    idfValues = new HashMap();
    TrainingData = new ArrayList();
    sg = new SummaryGenerator();

}

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