Tatiane M. Nogueira

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This work presents the integration of a fuzzy method and text mining to obtain an approach that enables the text documents classification to be closer to the user needs. The aim of this work is to develop a mechanism to reduce the high dimensionality of the attribute-value matrix obtained from the documents and, with this, to manage the imprecision and(More)
In this work, we present a method to generate, from text documents, fuzzy rules used to classify documents and to improve the information retrieval. With this method, we face the issue of dimensionality in text documents for information retrieval. We also present a comparison analysis among the method that we proposed and well-known machine learning methods(More)
The text mining process and its set of techniques have been widely used in order to look for new knowledge in textual documents, which can be recovered by information retrieval systems. There is a variety of methods developed to automatically organize documents based on the knowledge extracted from their content. The management of imprecision and(More)
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(More)
Ontologies have been successfully employed in applications that require semantic information processing. However, traditional ontologies are less suitable to express fuzzy or vague information, which often occurs in human vocabulary as well as in several application domains. In order to deal with such restriction, concepts from fuzzy set theory should be(More)
System flexibility means the ability of a system to manage imprecise and/or uncertain information. A lot of commercially available Information Retrieval Systems (IRS) address this issue at the level of query formulation. Another way to make the flexibility of an IRS possible is by means of the flexible organization of documents. Such organization can be(More)
Good cluster descriptors facilitate the efficient storage and retrieval of information. In particular, when the imprecision and uncertainty of textual information is considered, the extraction of cluster descriptors, which represent the compatibility of a document with a cluster in a more precise way, is a challenging problem. Therefore, in this paper we(More)
Ontologies have been successfully employed in applications that require semantic information processing. However, traditional ontologies are not able to express fuzzy or vague information, which often occurs in human vocabulary as well as in several application domains. In order to deal with such restriction, concepts of fuzzy set theory should be(More)
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,(More)
Ontologies have been employed in applications that require semantic information representation and processing. However, traditional ontologies are not suitable to express fuzzy or vague information, which often occurs in human vocabulary as well as in several application domains. To deal with this limitation, concepts from the Fuzzy Set Theory can be(More)