{'fraction_non_alphanumeric': 0.016129032258064516, 'fraction_numerical': 0.0021994134897360706, 'mean_word_length': 5.204545454545454, '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}}
TONE: A Method for Terminological Ontology Evaluation

Selecting the most appropriate candidate domain ontology is necessary to ensure that the ontology covers the domain of interest at a reasonable level of detail. Existing approaches have the following drawbacks:
 (1) Focused on the ontology coverage of concepts in the domain of interest, and ignored the semantic richness associated with each concept.
 (2) The ontology coverage metrics tend to select either large ontologies with broad scope or ontologies with a small number of concepts which may not capture a particular domain of interest.
 (3) The approaches are not robust in the coverage and semantic richness metric results when different term extraction and recognition algorithms are used.
 The limitations mentioned above will result in selecting ontologies which are not related to the domain of interest. Therefore, this paper presents a novel Terminological ONtology Evaluator (TONE). TONE uses a textual corpus to evaluate the ontology coverage and semantic richness. TONE was compared with existing ontology evaluation approaches and it proved that it was able to select the domain ontology which was intentionally developed to cover a specific domain of interest. In addition, TONE proved to be more robust in the coverage and semantic richness metric results compared to existing approaches.