{'fraction_non_alphanumeric': 0.017543859649122806, 'fraction_numerical': 0.0, 'mean_word_length': 5.0606060606060606, '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}}
An Improved K-Means Text Clustering Algorithm Based on Local Search

This paper presents a new text clustering algorithm based on local search and K-means (LSKM) and explains the characteristic of this algorithm theoretically. The experimental results of three standard test collections show that the new algorithm is better than K-means and the theoretical analysis is also testified in this paper.