The objective of this work is to improve the quality of the information that belongs to the database CubaCiencia, of the Institute of Scientific and Technological Information. This database has bibliographic information referring to four segments of science and is the main database of the Library Management System. The applied methodology was based on the Decision Trees, the Correlation Matrix, the 3D Scatter Plot, etc., which are techniques used by data mining, for the study of large volumes of information. The results achieved not only made it possible to improve the information in the database, but also provided truly useful patterns in the solution of the proposed objectives.
Este trabajo muestra los resultados alcanzados durante la búsqueda de patrones ocultos, aplicando algoritmos estadísticos, a una base de datos bibliográfica. Para esta investigación se seleccionó el software WinIDAMS v.1.3, que utiliza para el manejo de los datos la construcciónde un dataset IDAMS (BUILD) y la agrupación de datos (AGGREG), para el análisis estadístico los algoritmos Análisis de conglomerados (CLUSFIND) y los diagramas de dispersión (SCAT). Para las salidas de los resultados este software ofrece las tablas multidimensionales, capaces de crear por cada grupo de variables seleccionadas una tabla interna con resultados como la frecuencia y la media aritmética, que fueron las seleccionadas para estas pruebas, mientras que para la representación gráfica de los resultados se decidió utilizar los histogramas porque son gráficas de barras que permiten interpretar de forma muy fácil y rápida el comportamiento de las variables seleccionadas para el análisis. Este estudio encontró patrones a través de la clusterización con los cuales fue posible potenciar los servicios de difusión selectiva de la información y proponer nuevos servicios para que formen parte de los productos que brinda la biblioteca. This work shows the results obtained during the search for hidden patterns using statistical algorithms, in a bibliographic database. For this research the WinIDAMS v.1.3 software, used for data management, building an IDAMS dataset (BUILD) and Data Group (AGGREG) for statistical analysis algorithms, Cluster analysis was selected (CLUSFIND) and scatterplots (SCAT). In addition to the outputs of the results this software provides multidimensional tables, able to create for each group of selected variables, an internal table with results such as frequency and average arithmetic were selected for these tests, while for graphical representation of theresults, it was decided to use histograms, because they are bar graphs that allow us to interpret very easily and quickly, the behavior of the variables selected for analysis. This study found patterns through clustering, with which services could enhance Selective Dissemination of Information and propose new services, to become part of the products offered by the library.
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