{'fraction_non_alphanumeric': 0.017094017094017096, 'fraction_numerical': 0.0, 'mean_word_length': 5.632075471698113, '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}}
Extraction and Application of Cognitive Related Semantic Relationships

Unstructured knowledge extraction is the process of recognizing and storing valuable knowledge from the natural language texts. However, few tools are available to automatically extract knowledge concepts and their relations from the text books, especially for those in Chinese. This paper proposed a method to implement the ‘example of’ and ‘part of’ semantic relations' and their related entities' extracting from the digital textbooks in Chinese. The experimental data shows that the extraction of the both relations and the entities can achieve a rather high accuracy and satisfied results comparing with the previous studies.