Inductive Logic Programming - Info and Reading Options
12th International Conference, ILP 2002, Sydney, Australia, July 9-11, 2002. Revised Papers (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)
By Stan Matwin

"Inductive Logic Programming" is published by Springer in April 10, 2003 - Berlin, Heidelberg, it has 351 pages and the language of the book is English.
“Inductive Logic Programming” Metadata:
- Title: Inductive Logic Programming
- Author: Stan Matwin
- Language: English
- Number of Pages: 351
- Publisher: Springer
- Publish Date: April 10, 2003
- Publish Location: Berlin, Heidelberg
“Inductive Logic Programming” Subjects and Themes:
- Subjects: ➤ Logic programming - Congresses - Induktive Logik - INTELIGENCIA ARTIFICIAL - Kongress - Kunstmatige intelligentie - Logische Programmierung - Logisch programmeren - TEORIA E TECNICAS DE PROGRAMACʹAO
Edition Specifications:
- Format: Paperback
- Weight: 1.2 pounds
- Dimensions: 9.2 x 6.1 x 0.8 inches
Edition Identifiers:
- The Open Library ID: OL9894152M - OL16966725W
- Online Computer Library Center (OCLC) ID: 51566417
- Library of Congress Control Number (LCCN): 2003042482
- ISBN-13: 9783540005674 - 9783540364689
- ISBN-10: 3540005676
- All ISBNs: 3540005676 - 9783540005674 - 9783540364689
AI-generated Review of “Inductive Logic Programming”:
Snippets and Summary:
Automatically building conceptual classifications has been the subject of much research during the last twenty years (Michalski 81, German 89, De Raedt 01).
"Inductive Logic Programming" Description:
Open Data:
This book constitutes the thoroughly refereed post-proceedings of the 12th International Conference on Inductive Logic Programming, ILP 2002, held in Sydney, Australia in July 2002. The 22 revised full papers presented were carefully selected during two rounds of reviewing and revision from 45 submissions. Among the topics addressed are first order decision lists, learning with description logics, bagging in ILP, kernel methods, concept learning, relational learners, description logic programs, Bayesian classifiers, knowledge discovery, data mining, logical sequences, theory learning, stochastic logic programs, machine discovery, and relational pattern discovery
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