This book constitutes the refereed conference proceedings of the 30th International Conference on Inductive Logic Programming, ILP 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually.
The 16 papers and 3 short papers presented were carefully reviewed and selected from 19 submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data.
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Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed conference proceedings of the 30th International Conference on Inductive Logic Programming, ILP 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually.The 16 papers and 3 short papers presented were carefully reviewed and selected from 19 submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 296 pp. Englisch. Artikel-Nr. 9783030974534
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed conference proceedings of the 30th International Conference on Inductive Logic Programming, ILP 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 papers and 3 short papers presented were carefully reviewed and selected from 19 submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data. Artikel-Nr. 9783030974534
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