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                            [identifier] => oai:periodicos.ufpb.br:article/15128
                            [datestamp] => 2019-10-22T15:49:33Z
                            [setSpec] => ies:AR
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                                (
                                    [title] => Array
                                        (
                                            [0] => Information management in global environments: swarm intelligence in multilingual economic document repositories
                                            [1] => Gestión de la información en entornos globales: la inteligencia de enjambre en repositorios de documentos económicos multilingües
                                            [2] => Information Management in Global Environments:  Swarm Intelligence in multilingual economic document repositories
                                        )

                                    [creator] => Array
                                        (
                                            [0] => Cobo, Angel
                                            [1] => Rocha, Rocio
                                            [2] => Vanti, Adolfo Alberto
                                        )

                                    [subject] => Array
                                        (
                                            [0] => clustering
                                            [1] => ant-based algorithms
                                            [2] => multilingual documents
                                            [3] => text mining
                                            [4] => Agrupamiento. Algoritmos basados en hormigas
                                            [5] => Documentos multilíngües. Minería de texto.
                                            [6] => Clustering. Algoritmos baseados em formigas
                                            [7] => Documentos multilíngues. Mineração de texto.
                                        )

                                    [description] => Array
                                        (
                                            [0] => The information is a strategic resource of first order for organizations, so it is essential to have methodologies and tools that allow them to properly manage information and 
extract knowledge from it. Organizations also need knowledge generation strategies using unstructured textual information from different sources and in different languages. This paper 
presents two bio-inspired approaches to clustering multilingual document collections in a particular field (economics and business). This problem is quite significant and necessary to 
organize the huge volume of information managed within organisations in a global context characterised by the intensive use of Information and Communication Technologies. The proposed clustering algorithms take inspiration from the behaviour of real ant colonies and can be applied to identify groups of related multilingual documents in the field of economics and business. In order to obtain a language independent vector representation, several linguistic resources and tools are used. The performance of the algorithms is analysed using a corpus of 250 documents in Spanish and English from different functional areas of the enterprise, and experimental results are presented. The results demonstrate the usefulness and effectiveness of the algorithms as clustering technique.
                                            [1] => La información es un recurso estratégico de primer orden para cualquier organización, por lo que resulta esencial disponer de metodologías sistemáticas que permitan gestionarla adecuadamente y generar conocimiento a partir de ella. Además se requieren estrategias de generación de conocimiento a partir de información textual no estructurada procedente de diferentes fuentes y en diferentes idiomas. En este artículo se presentan dos enfoques bio-inspirados para el agrupamiento de documentos multilingües en el campo de la economía y los negocios. El problema abordado resulta de especial interés y necesario para organizar los grandes volúmenes de información que gestionan las organizaciones en un contexto global caracterizado por el uso intensivo de las tecnologías de la información y las comunicaciones. Los algoritmos de clustering propuestos se inspiran en el comportamiento observado en colonias de hormigas y pueden ser utilizados para identificar grupos de documentos relacionados escritos en diferentes idiomas dentro del ámbito de la economía y la administración de empresas. Con objeto de obtener una representación de los documentos independiente del idioma, se hace uso de diferentes recursos lingüísticos y herramientas. La efectividad de los algoritmos es analizada utilizando un corpus de 250 documentos escritos en español e inglés y vinculados con diferentes áreas funcionales de la empresa. Diferentes resultados experimentales son presentados, mostrando su usabilidad y eficiencia como técnicas de clustering documental.
                                            [2] => The information is a strategic resource of first order for organizations, so it is essential to have methodologies and tools that allow them to properly manage information and extract knowledge from it. Organizations also need knowledge generation strategies using unstructured textual information from different sources and in different languages. This paper presents two bio-inspired approaches to clustering multilingual document collections in a particular field (economics and business). This problem is quite significant and necessary to organize the huge volume of information managed within organisations in a global context characterised by the intensive use of Information and Communication Technologies. The proposed clustering algorithms take inspiration from the behaviour of real ant colonies and can be applied to identify groups of related multilingual documents in the field of economics and business. In order to obtain a language independent vector representation, several linguistic resources and tools are used. The performance of the algorithms is analysed using a corpus of 250 documents in Spanish and English from different functional areas of the enterprise, and experimental results are presented. The results demonstrate the usefulness and effectiveness of the algorithms as clustering technique.
                                        )

                                    [publisher] => UFPB
                                    [date] => 2013-05-10
                                    [type] => Array
                                        (
                                            [0] => info:eu-repo/semantics/article
                                            [1] => info:eu-repo/semantics/publishedVersion
                                        )

                                    [format] => application/pdf
                                    [identifier] => https://periodicos.ufpb.br/ojs2/index.php/ies/article/view/15128
                                    [source] => Array
                                        (
                                            [0] => Informação & Sociedade; Vol. 23 No. 1 (2013)
                                            [1] => Informação & Sociedade; Vol. 23 Núm. 1 (2013)
                                            [2] => Informação & Sociedade; v. 23 n. 1 (2013)
                                            [3] => 1809-4783
                                            [4] => 0104-0146
                                        )

                                    [language] => por
                                    [relation] => https://periodicos.ufpb.br/ojs2/index.php/ies/article/view/15128/9288
                                )

                        )

                )

        )

)