{'fraction_non_alphanumeric': 0.016317016317016316, 'fraction_numerical': 0.0, 'mean_word_length': 5.458646616541353, '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}}
Rules for describing multi-attribute information and its efficient pattern matching

This paper describes an efficient multi-attribute pattern matching machine to locate all occurrences of any of a finite number of sequences of rule structures in a series of input structures. The proposed machine has the following distinctive features: it can match set representations containing multiple attributes; it also enables us to match separate components; and it can match a rule consisting of an exclusive set. In this paper, these features are described in detail. Moreover, the pattern matching algorithm is evaluated by the theoretical evaluation and the experimental evaluation that are supported by the simulation results for a variety of rules for document processing, such as text proofreading, text reduction, and examining a relation between sentences.