{'fraction_non_alphanumeric': 0.014285714285714285, 'fraction_numerical': 0.002197802197802198, 'mean_word_length': 5.2827586206896555, '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}}
Fast plagiarism detection based on simple document similarity

Plagiarism detection in a large number of documents requires efficient methods. This paper proposes a plagiarism detection algorithm based on approximate string matching to be specified in “copy and paste”-type plagiarisms, and a speed improvement to an implementation of the algorithm. Most of the computations required in the algorithm are omitted by two kinds of approximations of the output used for plagiarism detection, while the decrease of accuracy caused by the approximations is acceptable. The effect of the improvement on the processing time and accuracy of the algorithm is evaluated by conducting experiments with a data set. The experimental results show that the improvement can reduce the processing time to approximately one-twentieth for a 6.4% decrease of the accuracy from those for the normal implementation of the algorithm.