Multimedia Search and Temporal Reasoning
Marcio Ferreira Moreno, Rodrigo Costa Mesquita Santos, Wallas Henrique, Sousa dos Santos, Sandro Rama Fiorini, Reinaldo Mozart da Gama Silva
TL;DR
This paper introduces a temporal query language and engine within the hyperknowledge framework to better model and reason about dynamic, time-dependent information, validated through a real-world Oil & Gas case study.
Contribution
It extends the hyperknowledge framework with temporal reasoning capabilities and proposes a new query language, addressing limitations of current knowledge bases in representing time-specific relationships.
Findings
Effective modeling of temporal facts demonstrated in Oil & Gas case
Enhanced query capabilities for dynamic information
Framework supports reasoning over time-dependent data
Abstract
Properly modelling dynamic information that changes over time still is an open issue. Most modern knowledge bases are unable to represent relationships that are valid only during a given time interval. In this work, we revisit a previous extension to the hyperknowledge framework to deal with temporal facts and propose a temporal query language and engine. We validate our proposal by discussing a qualitative analysis of the modelling of a real-world use case in the Oil & Gas industry.
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