{'fraction_non_alphanumeric': 0.013220018885741265, 'fraction_numerical': 0.0, 'mean_word_length': 5.751592356687898, '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}}
Fuzzy cluster descriptors improve flexible organization of documents

System flexibility means the ability of a system to manage imprecise and/or uncertain information. There are two ways to address the Information Retrieval Systems (IRS) flexibility: through methods that improve the query formulation and through methods that improve the document organization. Since the query formulation has obtained more attention in retrieval process, we aim to investigate the flexibility in document organization. When a document organization is carried out using fuzzy clustering, the documents can belong to more than one cluster simultaneously with different membership degrees, allowing the management of imprecise and/or uncertain information in the collection organization. Clusters represent topics and are identified by one or more descriptors. In this work we use an unsupervised method to extract cluster descriptors for a specific database and investigate whether the quality of the fuzzy cluster descriptors improves the flexible organization of documents.