Inductive Logic Programming [[electronic resource] ] : 13th International Conference, ILP 2003, Szeged, Hungary, September 29 - October 1, 2003, Proceedings / / edited by Tamas Horváth, Akihiro Yamamoto

• Record Nr.: UNISA996465800003316
• Pubbl/distr/stampa: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003
• ISBN: 3-540-39917-8
• Edizione: [1st ed. 2003.]
• Descrizione fisica: 1 online resource (X, 406 p.)
• Collana: Lecture Notes in Artificial Intelligence ; ; 2835
• Disciplina: 05.115
• Soggetti: Software engineering; Artificial intelligence; Computer science; Computer programming; Mathematical logic; Software Engineering/Programming and Operating Systems; Artificial Intelligence; Computer Science, general; Programming Techniques; Mathematical Logic and Formal Languages
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
• Nota di contenuto: Invited Papers -- A Personal View of How Best to Apply ILP -- Agents that Reason and Learn -- Research Papers -- Mining Model Trees: A Multi-relational Approach -- Complexity Parameters for First-Order Classes -- A Multi-relational Decision Tree Learning Algorithm – Implementation and Experiments -- Applying Theory Revision to the Design of Distributed Databases -- Disjunctive Learning with a Soft-Clustering Method -- ILP for Mathematical Discovery -- An Exhaustive Matching Procedure for the Improvement of Learning Efficiency -- Efficient Data Structures for Inductive Logic Programming -- Graph Kernels and Gaussian Processes for Relational Reinforcement Learning -- On Condensation of a Clause -- A Comparative Evaluation of ; Feature Set Evolution Strategies for Multirelational Boosting -- Comparative Evaluation of Approaches to Propositionalization -- Ideal Refinement of Descriptions in -Log -- Which First-Order Logic Clauses Can Be Learned Using Genetic Algorithms? -- Improved Distances for Structured Data -- Induction of Enzyme Classes from Biological Databases -- Estimating Maximum Likelihood Parameters for Stochastic Context-Free Graph Grammars -- Induction of the Effects of Actions by Monotonic Methods -- Hybrid Abductive Inductive Learning: A Generalisation of Progol -- Query Optimization in Inductive Logic Programming by Reordering Literals -- Efficient Learning of Unlabeled Term Trees with Contractible Variables from Positive Data -- Relational IBL in Music with a New Structural Similarity Measure -- An Effective Grammar-Based Compression Algorithm for Tree Structured Data.