A Graph DB-Based Solution for Semantic Technologies in the Future Internet

Abstract

With the progressive improvements in the power, effectiveness, and reliability of AI solutions, more and more critical human problems are being handled by automated AI-based tools and systems. For more complex or particularly critical applications, the level of knowledge, not just information, must be handled by systems where explicit relationships among objects are represented and processed. For this purpose, the knowledge representation branch of AI proposes Knowledge Graphs, widely used in the Semantic Web, where different online applications may interact by understanding the meaning of the data they process and exchange. This paper describes a framework and online platform for the Internet-based knowledge graph definition, population, and exploitation based on the LPG graph model. Its main advantages are its efficiency and representational power and the wide range of functions that it provides to its users beyond traditional Semantic Web reasoning: network analysis, data mining, multistrategy reasoning, and knowledge browsing. Still, it can also be mapped onto the SW.

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“…Ref. [71] Ferilli et al's investigation into a graph database-based approach for semantic technologies in the Internet of the future presents a viable path for improving data interpretation and connectivity, which is essential for the development of the semantic web. [72] A major contribution to our understanding of blockchain's financial features is made by Marin et al, who offer a thorough analysis of blockchain tokens and throw light on their formation, pricing, and wider implications for digital economies.…”