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[null,"1.","Record Nr.",null,"UNISA996466245703316"]
[null,null,"Titolo",null,"Inductive Logic Programming [[electronic resource] ] : 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007,  Revised Selected Papers / / edited by Hendrik Blockeel, Jan Ramon, Jude Shavlik, Prasad Tadepalli"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008"]
[null,null,"ISBN",null,"3-540-78469-1"]
[null,null,"Edizione",null,"[1st ed. 2008.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XI, 307 p.)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence ; ; 4894"]
[null,null,"Disciplina",null,"005.1/5"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Software engineering"]
[{"$nulls":4},"Computer programming"]
[{"$nulls":4},"Mathematical logic"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Software Engineering/Programming and Operating Systems"]
[{"$nulls":4},"Programming Techniques"]
[{"$nulls":4},"Mathematical Logic and Formal Languages"]
[{"$nulls":4},"Algorithm Analysis and Problem Complexity"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Invited Talks -- Learning with Kernels and Logical Representations -- Beyond Prediction: Directions for Probabilistic and Relational Learning -- Extended Abstracts -- Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract) -- Learning Directed Probabilistic Logical Models Using Ordering-Search -- Learning to Assign Degrees of Belief in Relational Domains -- Bias/Variance Analysis for Relational Domains -- Full Papers -- Induction of Optimal Semantic Semi-distances for Clausal Knowledge Bases -- Clustering Relational Data Based on Randomized Propositionalization -- Structural Statistical Software Testing with Active Learning in a Graph -- Learning Declarative Bias -- ILP :- Just Trie It -- Learning Relational Options for "]
[{"$nulls":4},"Inductive Transfer in Relational Reinforcement Learning -- Empirical Comparison of “Hard” and “Soft” Label Propagation for Relational Classification -- A Phase Transition-Based Perspective on Multiple Instance Kernels -- Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates -- Applying Inductive Logic Programming to Process Mining -- A Refinement Operator Based Learning Algorithm for the Description Logic -- Foundations of Refinement Operators for Description Logics -- A Relational Hierarchical Model for Decision-Theoretic Assistance -- Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming -- Revising First-Order Logic Theories from Examples Through Stochastic Local Search -- Using ILP to Construct Features for Information Extraction from Semi-structured Text -- Mode-Directed Inverse Entailment for Full Clausal Theories -- Mining of Frequent Block Preserving Outerplanar Graph Structured Patterns -- Relational Macros for Transfer in Reinforcement Learning -- Seeing the Forest Through the Trees -- Building Relational World Models for Reinforcement Learning -- An Inductive Learning System for XML Documents."]