{'fraction_non_alphanumeric': 0.014985014985014986, 'fraction_numerical': 0.0, 'mean_word_length': 6.1063829787234045, '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}}
Research on Intelligent Natural Language Texts Classification

—Natural language texts widely exist in many aspects of social life, and classification is of great significance to its efficient use and normalized preservation. Manual texts classification has the problems such as labor intensive, experience dependent and error prone, therefore, the research on intelligent classification of natural language texts has great social value. In recent years, machine learning technology has developed rapidly, and related researchers have carried out a lot of works on the texts classification based on machine learning, the research methods show the characteristic of diversification. This paper summarizes and compares the texts classification methods mainly from three aspects, including technical routes, text vectorization methods and classification information processing methods, in order to provide references for further research and explore the development direction of the texts classification.