{'fraction_non_alphanumeric': 0.018083182640144666, 'fraction_numerical': 0.0, 'mean_word_length': 5.325714285714286, '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}}
Digital information mining technology based on principal component analysis

With the evolution of large computer data, every corner of the society is filled with a variety of text information. Indeed, large data information that need manage by people has been unable to meet the rapid development of society. Therefore, the technology of efficient management and accurate positioning of vast quantities of text information has become a hot topic in the research community. In this article, we use principal component analysis (PCA) to deal with the text data. The principle of principal component analysis, which has the least principle of data loss, replaces more variables with fewer synthetic variables. Indeed, our approach both reduces the dimensions of the original data variables, eliminates the correlation of the input variables, and improve the processing speed of digital information. Using principal component analysis and K - average algorithm of combining the method of original data preprocessing, the experimental results also verify the effectiveness of the proposed method in this paper.