f522e894852f28da0d6b9441ce8e49f486dfbc5f,conceptnet5/vectors/transforms.py,,choose_small_vocabulary,#,149

Before Change

     - are not in ConceptNet
    
    concepts = set(line.strip() for line in open(concepts_filename))
    small_vocab = [term for term in big_frame.index if term.count("_") < 1 and term in concepts]
    return small_vocab


def make_big_frame(frame, language):

After Change

     - are not frequent
    
    concepts = set(line.strip() for line in open(concepts_filename))
    vocab = []
    for term in big_frame.index:
        if "_" not in term and term in concepts:
            frequency = word_frequency(uri_to_label(term), language, wordlist="large")
            vocab.append((term, frequency))
    small_vocab = [term for term, frequency in sorted(vocab, key=lambda x: x[1], reverse=True)[
                                               :50000]]
    return small_vocab


def make_big_frame(frame, language):

Instances