Abstract
This tutorial gives an overview of current methods for performing reasoning on very large knowledge bases. The first part of the lectures is dedicated to an introduction of the problem and of related technologies. Then, the tutorial continues discussing the state-of-the-art for reasoning on very large inputs with particular emphasis on the strengths and weaknesses of current approaches. Finally, the tutorial concludes with an outline of some of the most important research directions in this field.
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Urbani, J. (2018). Reasoning at Scale (Tutorial). In: d’Amato, C., Theobald, M. (eds) Reasoning Web. Learning, Uncertainty, Streaming, and Scalability. Reasoning Web 2018. Lecture Notes in Computer Science(), vol 11078. Springer, Cham. https://doi.org/10.1007/978-3-030-00338-8_9
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