scholarly journals Búsqueda de patrones para mejorar productos y servicios en las bibliotecas

2017 ◽  
Vol 31 (72) ◽  
pp. 209
Author(s):  
Esther Marina Ruiz Lobaina ◽  
Pedro Lázaro Romero Suárez
Keyword(s):  
Cluster Analysis ◽  
Statistical Analysis ◽  
Data Management ◽  
Graphical Representation ◽  
Bibliographic Database ◽  
Statistical Algorithms ◽  
Hidden Patterns ◽  
Selective Dissemination Of Information ◽  
Data Group ◽  
Bar Graphs

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.

SELECTIVE DISSEMINATION OF INFORMATION (SDI)

1966 ◽  
Author(s):  
ARMY ELECTRONICS COMMAND FORT MONMOUTH NJ
Keyword(s):  
Selective Dissemination Of Information

SELECTIVE DISSEMINATION OF INFORMATION USING A KDF9 COMPUTER

1968 ◽  
Vol 20 (1) ◽  
pp. 40-64 ◽  
Author(s):  
L.J. ANTHONY ◽  
D.H. CARPENTER ◽  
A.G. CHENEY
Keyword(s):  
Selective Dissemination Of Information

Library Management Systems in Legal Libraries

2003 ◽  
Vol 3 (3-4) ◽  
pp. 196-198
Author(s):  
Emma Duffield
Keyword(s):  
Management Systems ◽  
The Internet ◽  
Access To Information ◽  
Legal Information ◽  
Library Management ◽  
Library Automation ◽  
Web Resources ◽  
Library Management System ◽  
Library Catalogue ◽  
Selective Dissemination Of Information

Legal libraries, by their very nature, have highly specialised requirements when it comes to library automation. A traditional library management system, which will simply catalogue books and provide the means to issue them to borrowers for a defined period, will not provide the flexibility required by a modern legal information centre. Serials management, direct links to web resources and the selective dissemination of information are of far more importance to a legal library than whether a loan is overdue. Access to information is crucial – the library catalogue needs to be available to researchers wherever they are, whether sitting at their desks or accessing the data via the internet.

Human-centric Faceted Approach for Ontology Construction

2020 ◽  
Vol 47 (1) ◽  
pp. 31-44
Author(s):  
Shiv Shakti Ghosh ◽  
Subhashis Das ◽  
Sunil Kumar Chatterjee
Keyword(s):  
Domain Knowledge ◽  
Information Science ◽  
Library And Information Science ◽  
Construction Process ◽  
Information Need ◽  
Ontology Construction ◽  
System P ◽  
Facet Analysis ◽  
Tourism Information ◽  
Selective Dissemination Of Information

In this paper, we propose an ontology building method, called human-centric faceted approach for ontology construction (HCFOC). HCFOC uses the human-centric approach, improvised with the idea of selective dissemination of information (SDI), to deal with context. Further, this ontology construction process makes use of facet analysis and an analytico-synthetic classification approach. This novel fusion contributes to the originality of HCFOC and distinguishes it from other existing ontology construction methodologies. Based on HCFOC, an ontology of the tourism domain has been designed using the Protégé-5.5.0 ontology editor. The HCFOC methodology has provided the necessary flexibility, extensibility, robustness and has facilitated the capturing of background knowledge. It models the tourism ontology in such a way that it is able to deal with the context of a tourist’s information need with precision. This is evident from the result that more than 90% of the user’s queries were successfully met. The use of domain knowledge and techniques from both library and information science and computer science has helped in the realization of the desired purpose of this ontology construction process. It is envisaged that HCFOC will have implications for ontology developers. The demonstrated tourism ontology can support any tourism information retrieval system.

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