Knowledge Graphs: A Tutorial on the History of Knowledge Graph's Main Ideas

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Abstract

Knowledge Graphs can be considered as fulfilling an early vision in Computer Science of creating intelligent systems that integrate knowledge and data at large scale. Stemming from scientific advancements in research areas of Semantic Web, Databases, Knowledge representation, NLP, Machine Learning, among others, Knowledge Graphs have rapidly gained popularity in academia and industry in the past years. The integration of such disparate disciplines and techniques give the richness to Knowledge Graphs, but also present the challenge to practitioners and theoreticians to know how current advances develop from early techniques in order, on one hand, take full advantage of them, and on the other, avoid reinventing the wheel. This tutorial will provide a historical context on the roots of Knowledge Graphs grounded in the advancements of Logic, Data and the combination thereof.

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Gutierrez, C., & Sequeda, J. F. (2020). Knowledge Graphs: A Tutorial on the History of Knowledge Graph’s Main Ideas. In International Conference on Information and Knowledge Management, Proceedings (pp. 3509–3510). Association for Computing Machinery. https://doi.org/10.1145/3340531.3412176

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