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.
@article{arxiv.1911.08225,
title = {Multimedia Search and Temporal Reasoning},
author = {Marcio Ferreira Moreno and Rodrigo Costa Mesquita Santos and Wallas Henrique Sousa dos Santos and Sandro Rama Fiorini and Reinaldo Mozart da Gama Silva},
journal= {arXiv preprint arXiv:1911.08225},
year = {2019}
}
Comments
International Conference on Information Systems (ICIS) 2019