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Abstract

Knowledge Organization Systems, even traditional ones, such as the Universal Decimal Classification, have been studied to improve the retrieval of information online, although the potential of using knowledge structures in the user interface has not yet been widespread. Objective: This study presents a mapping of scientific production on information retrieval methodologies, which make use of the Universal Decimal Classification. Methodology: Systematic Literature Review, conducted in two stages, with a selection of 44 publications, resulting in the time interval from 1964 to 2017, whose categories analyzed were: most productive authors, languages of publications, types of document, year of publication, most cited work, major impact journal, and thematic categories covered in the publications. Results: A total of nine more productive authors and co-authors were found; predominance of the English language (42 publications); works published in the format of journal articles (33); and highlight to the year 2007 (eight publications). In addition, it was identified that the most cited work was by Mcilwaine (1997), with 61 citations, and the journal Extensions & Corrections to the UDC was the one with the largest number of publications, in addition to the incidence of the theme Universal Automation linked to a thesaurus for information retrieval, present in 19 works. Conclusions: Shortage of studies that explore the potential of the Decimal Classification, especially in Brazilian literature, which highlights the need for further study on the topic, involving research at the national and international levels.

Theme

Klassifikationssysteme im Online-Retrieval

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Footnote

Übers. d. Titels: Interface for retrieval from online access catalogues with ranked results according to their relevance

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Abstract

Several instruments of knowledge organization will reflect different possibilities for information retrieval. In this context, ontologies have a different potential because they allow knowledge discovery, which can be used to retrieve information in a more flexible way. However, this potential can be affected by the theoretical principles adopted in ontology building. The aim of this paper is to discuss, in an introductory way, how a (not exhaustive) set of theoretical principles can influence an aspect of ontologies: their use to obtain inferences. In this context, the role of Ingetraut Dahlberg's Theory of Concept is discussed. The methodology is exploratory, qualitative, and from the technical point of view it uses bibliographic research supported by the content analysis method. It also presents a small example of application as a proof of concept. As results, a discussion about the influence of conceptual definition on subsumption inferences is presented, theoretical contributions are suggested that should be used to guide the formation of hierarchical structures on which such inferences are supported, and examples are provided of how the absence of such contributions can lead to erroneous inferences

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Abstract

Information management in corporate environments is a growing problem as companies' information assets grow and their need to use them in their operations. Several management models have been practiced with application on the most diverse fronts, practices that integrate the so-called Enterprise Content Management. This study proposes a conceptual model of semantic corporate information ecosystem, based on the Universal Document Model proposed by Dagobert Soergel. It focuses on unstructured information objects, especially multimedia, increasingly used in corporate environments, adding semantics and expanding their recovery potential in the composition and reuse of dynamic documents on demand. The proposed model considers stable elements in the organizational environment, such as actors, processes, business metadata and information objects, as well as some basic infrastructures of the corporate information environment. The main objective is to establish a conceptual model that adds semantic intelligence to information assets, leveraging pre-existing infrastructure in organizations, integrating and relating objects to other objects, actors and business processes. The approach methodology considered the state of the art of Information Organization, Representation and Retrieval, Organizational Content Management and Semantic Web technologies, in the scientific literature, as bases for the establishment of an integrative conceptual model. Therefore, the research will be qualitative and exploratory. The predicted steps of the model are: Environment, Data Type and Source Definition, Data Distillation, Metadata Enrichment, and Storage. As a result, in theoretical terms the extended model allows to process heterogeneous and unstructured data according to the established cut-outs and through the processes listed above, allowing value creation in the composition of dynamic information objects, with semantic aggregations to metadata.