{'fraction_non_alphanumeric': 0.01347305389221557, 'fraction_numerical': 0.0, 'mean_word_length': 5.371428571428571, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Using the Mesh Hierarchy to Index Bioinformatics Articles

As the number of bioinformatics articles increase, the ability to classify them into a structured hierarchy grows more important. For purposes such as text retrieval or knowledge discovery, it is useful organize articles based on content. In this study, we evaluate a new method for hierarchical classification of abstracts from bioinformatics articles according to MeSH terms. We compare our method against a flat classifier as a baseline, and find that although performance on exact index assignment is weaker, the hierarchical classifier more often makes predictions in the correct branch of the hierarchy.