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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): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 9575 | Lecture Notes in Computer Science ; 9575Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016Description: X, 215 p. 56 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319405667
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 005.131 23
LOC classification:
  • QA8.9-10.3
Online resources: In: 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.
Item type: E-BOOKS
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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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The Institute of Mathematical Sciences, Chennai, India