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Inductive Logic Programming = 29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3–5, 2019, Proceedings /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Inductive Logic Programming/ edited by Dimitar Kazakov, Can Erten.
其他題名:	29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3–5, 2019, Proceedings /
其他作者:	Erten, Can.
面頁冊數:	IX, 145 p. 125 illus., 19 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Information Systems and Communication Service. -
電子資源:	https://doi.org/10.1007/978-3-030-49210-6
ISBN:	9783030492106

Inductive Logic Programming = 29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3–5, 2019, Proceedings /
Inductive Logic Programming29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3–5, 2019, Proceedings /[electronic resource] :edited by Dimitar Kazakov, Can Erten. - 1st ed. 2020. - IX, 145 p. 125 illus., 19 illus. in color.online resource. - Lecture Notes in Artificial Intelligence ;11770. - Lecture Notes in Artificial Intelligence ;9285.

CONNER: A Concurrent ILP Learner in Description Logic -- Towards Meta-interpretive Learning of Programming Language Semantics -- Towards an ILP Application in Machine Ethics -- On the Relation Between Loss Functions and T-Norms -- Rapid Restart Hill Climbing for Learning Description Logic Concepts -- Neural Networks for Relational Data -- Learning Logic Programs from Noisy State Transition Data -- A New Algorithm for Computing Least Generalization of a Set of Atoms -- LazyBum: Decision Tree Learning Using Lazy Propositionalization -- Weight Your Words: the Effect of Different Weighting Schemes on Wordification Performance -- Learning Probabilistic Logic Programs over Continuous Data.

This book constitutes the refereed conference proceedings of the 29th International Conference on Inductive Logic Programming, ILP 2019, held in Plovdiv, Bulgaria, in September 2019. The 11 papers presented were carefully reviewed and selected from numerous 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.

ISBN: 9783030492106

Standard No.: 10.1007/978-3-030-49210-6doiSubjects--Topical Terms:

669203
Information Systems and Communication Service.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

Inductive Logic Programming = 29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3–5, 2019, Proceedings /
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