Inductive Logic Programming [electronic resource] : 25th International Conference, ILP 2015, Kyoto, Japan, August 20-22, 2015, Revised Selected Papers / edited by Katsumi Inoue, Hayato Ohwada, Akihiro Yamamoto.
Contributor(s): Inoue, Katsumi [editor.]
| Ohwada, Hayato [editor.] | Yamamoto, Akihiro [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Artificial Intelligence: 9575Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: X, 215 p. 56 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319405667.Subject(s): Machine theory | Artificial intelligence | Computer programming | Computer science | Data mining | Formal Languages and Automata Theory | Artificial Intelligence | Programming Techniques | Computer Science Logic and Foundations of Programming | Data Mining and Knowledge DiscoveryAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 005.131 Online resources: Click here to access online
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Springer Nature eBookSummary: This book constitutes the thoroughly refereed post-conference proceedings of the 25th International Conference on Inductive Logic Programming, ILP 2015, held in Kyoto, Japan, in August 2015. The 14 revised papers presented were carefully reviewed and selected from 44 submissions. The papers focus on topics such as theories, algorithms, representations and languages, systems and applications of ILP, and cover all areas of learning in logic, relational learning, relational data mining, statistical relational learning, multi-relational data mining, relational reinforcement learning, graph mining, connections with other learning paradigms, among others.
This book constitutes the thoroughly refereed post-conference proceedings of the 25th International Conference on Inductive Logic Programming, ILP 2015, held in Kyoto, Japan, in August 2015. The 14 revised papers presented were carefully reviewed and selected from 44 submissions. The papers focus on topics such as theories, algorithms, representations and languages, systems and applications of ILP, and cover all areas of learning in logic, relational learning, relational data mining, statistical relational learning, multi-relational data mining, relational reinforcement learning, graph mining, connections with other learning paradigms, among others.
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