{'fraction_non_alphanumeric': 0.028720626631853787, 'fraction_numerical': 0.0, 'mean_word_length': 5.286885245901639, '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}}
Building Folk UMLS: An Approach to Finding Meaning of Folk Terms in Medical Domain

As a medical domain knowledge base, the Unified Medical Language System (UMLS) focuses on formal and professional medical terms; online health forums contain user-generated “folk terms”, which can be used to complement the UMLS vocabulary. In this paper, we propose an approach to detecting folk terms from online discussions and matching their meanings to UMLS concepts. This approach makes connections between expert-built ontology and user-generated taxonomy (folksonomy) based on term distance matching using Google distance measurement. By finding meanings of user-generated folk terms, we will build what we call “folk UMLS” ontology as enrichment to the formal UMLS ontology.