Example usage for org.apache.commons.collections4.map MultiValueMap get

Introduction

In this page you can find the example usage for org.apache.commons.collections4.map MultiValueMap get.

Prototype

Object get(Object key);

Source Link

Document

Gets the collection of values associated with the specified key.

Usage

From source file:com.farhad.ngram.lang.detector.profile.LanguageProfile.java

public void construct(String path) {
    MultiValueMap corpus = filetools.readFile(path);

    Iterator<String> it = corpus.keySet().iterator();

    Map<String, Map> profile = new ConcurrentHashMap<>();

    //iterate over each class
    while (it.hasNext()) {

        String theKey = (String) it.next();

        List<String> texts = (List<String>) corpus.get(theKey);
        Num_Docs = texts.size();/*from   w w  w  . ja  va  2 s  .  co m*/
        Map<Integer, Map> ngrams_lang = new HashMap<Integer, Map>();

        Map<String, MyPair> ngrams_profile = new ConcurrentHashMap<>();

        //iterate over each text
        for (int i = 0; i < texts.size(); i++) {

            String text = texts.get(i);
            Map<String, Integer> grams = new HashMap<>();
            for (int n = 1; n <= ngrams; n++) {

                grams.putAll(NgramExtractor.gramLength(n).extractCountedGrams(text));

            }

            ngrams_lang.put(i, grams);

        }

        Iterator<Integer> itt = ngrams_lang.keySet().iterator();

        while (itt.hasNext()) {

            Map<String, Integer> ngram = ngrams_lang.get(itt.next());
            Iterator<String> ittt = ngram.keySet().iterator();

            while (ittt.hasNext()) {

                String ng = ittt.next();

                if (ngrams_profile.containsKey(ng)) {

                    MyPair pair = ngrams_profile.get(ng);
                    pair.setFirst(pair.getFirst() + ngram.get(ng));
                    pair.setSecond(pair.getSecond() + 1);
                    ngrams_profile.put(ng, pair);

                } else {

                    MyPair pair = new MyPair(ngram.get(ng), 1);
                    ngrams_profile.put(ng, pair);
                }
            }
        }

        profile.put(theKey, ngrams_profile);

    }

    //filter based on doc_frequency and term_frequency 
    Iterator<String> p_it = profile.keySet().iterator();

    while (p_it.hasNext()) {

        String lang = p_it.next();
        List<String> texts = (List<String>) corpus.get(lang);
        Num_Docs = texts.size();

        Map<String, MyPair> ngram = profile.get(lang);

        Iterator<String> ngram_it = ngram.keySet().iterator();
        while (ngram_it.hasNext()) {
            String key = ngram_it.next();
            MyPair freq = ngram.get(key);
            if (freq.getFirst() <= MIN_TERM_FREQUENCY | freq.getSecond() >= Num_Docs) {
                ngram.remove(key);
            }

        }

    }

    //computer the term frequecny for each n-gram 
    p_it = profile.keySet().iterator();

    while (p_it.hasNext()) {
        String lang = p_it.next();
        List<String> texts = (List<String>) corpus.get(lang);
        Num_Docs = texts.size();

        Map<String, MyPair> ngram = profile.get(lang);

        int N = ngram.keySet().size();

        Iterator<String> ngram_it = ngram.keySet().iterator();
        Map<String, Double> ngram_tfidf = new HashMap<>();

        while (ngram_it.hasNext()) {

            String key = ngram_it.next();
            MyPair freq = ngram.get(key);

            double tf = (double) freq.getFirst() / N;
            ngram_tfidf.put(key, tf);

        }

        //write the language profile 
        String filename = lang + ".profile";
        saveProfile(filename, ngram_tfidf);
    }
}

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