Systems for automatic indexing by assignment: a comparative analysis

• Autor(a) principal: Silva, Sâmela Rouse de Brito
• Data de Publicação: 2020
• Outros Autores: Correa, Renato Fernandes
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Encontros Bibli
• Texto Completo: https://periodicos.ufsc.br/index.php/eb/article/view/1518-2924.2020.e70740
• topic: Indexação Automática; Indexação Automática por Atribuição; Sistema de Indexação Automática; Processamento de Linguagem Natural; Recuperação da Informação; Automatic Indexing; Automatic Indexing by Assignment; Automatic Indexing Systems; Natural Language Processing; Information retrieval

Objective: This work presents a comparative analysis between two multilingual automatic indexing systems that perform term assignment: SISA and MAUI. The SISA (Semi-automatic Indexing System) made in Spain and initially proposed for the area of Librarianship and Documentation, it is a specialist system that automatically indexes following a thesaurus and predetermined rules of indexation which are based on the frequency and position of the terms. The MAUI (Multi-purpose Automatic Topic Indexing) is a system of New Zealand origin that presents the specificity of use of a thesaurus and algorithm of machine learning to generate model through the results of the intellectual indexing, being the terms represented by statistical features. Methods: The research is exploratory and bibliographical, where the method used to construct this work was the comparative study based on content analysis of the scientific publications containing experience reports of application of that software. The stages of the research consisted of describing and comparing the characteristics of each system, raising information about how the documents are processed, how the systems performs the extraction and selection of the descriptors terms, and the application context. Results: The results show the   approaches, main operations, the resources used by each system during the automatic indexing process, as well as the application context and quality of results. Conclusions: It hopes to contribute to the studies on the topic of automatic indexing in the deepening discussion about descriptive and comparative categories related to methods and techniques implemented in the systems.