Methodological proposal for knowledge network exploration in a graph database of CENACE’s Knowledge Management System
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Abstract
This paper presents a methodological proposal for data exploration through graph theory, which has been applied for the capture, validation and storage of knowledge, as a practical issue in the National Electricity Operator, CENACE. For this proposal, knowledge, knowledge management, human capital management and graph theory are considered as the basis for creating a knowledge network that allows data processing, network analysis, relationships, and graphical results that allow decision-making in an effective and efficient way, optimizing resources and innovating the way of presenting results from relational databases into graphic databases. The present work applies a methodology based on graph theory and the description of the graphical structural models, which has allowed generating study models and obtaining valid and reliable results, through a Neo4j database tool, an application that allows graphing the connections found in the social data analysis. The scientific contribution of this technical work is settled on the capture of knowledge and presentation of reports that allow generating value added in terms of knowledge management, creating a competitive advantage for the Institution.
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