Abstract
A powerful and flexible organization of documents can be obtained by mixing fuzzy and possibilistic clustering. In such organization, documents can belong to more than one cluster simultaneously with different compatibility degrees. Clusters represent topics, which are identified by one or more descriptors extracted by a proposed method. In this manuscript, we investigated whether or not the descriptors extracted after applying possibilistic fuzzy clustering improve the flexible organization of documents. Experiments were carried out on real-world document collections and we evaluated the ability of descriptors to capture the essential information in every dataset. Results have shown the effectiveness of extracting possibilistic fuzzy cluster descriptors, improving the flexible organization of documents.
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