02984nam 2200709Ia 450 991078425420332120230829000822.066107048211-280-70482-997866107048281-4294-5527-61-60750-207-0600-00-0341-21-4337-0124-39781586036744(CKB)1000000000340144(EBL)280881(OCoLC)228146682(SSID)ssj0000178507(PQKBManifestationID)11197344(PQKBTitleCode)TC0000178507(PQKBWorkID)10221976(PQKB)11008587(MiAaPQ)EBC280881(Au-PeEL)EBL280881(CaPaEBR)ebr10152505(CaONFJC)MIL70482(EXLCZ)99100000000034014420070117d2006 uy 0engur|n|---|||||txtccrAn inductive logic programming approach to statistical relational learning[electronic resource] /Kristian KerstingAmsterdam ;Washington, D.C. IOS Pressc20061 online resource (256 p.)Frontiers in artificial intelligence and applications ;v. 148Dissertations in artificial intelligenceDescription based upon print version of record.1-58603-674-2 Includes bibliographical references (p. 201-221) and index.Title page; Contents; Abstract; Overture; Part I: Probabilistic ILP over Interpretations; Part II: Probabilistic ILP over Time; Intermezzo: Exploiting Probabilistic ILP in Discriminative Classifiers; Part III: Making Complex Decisions in Relational Domains; Finale; Appendix; Bibliography; Symbol Index; IndexTalks about Logic Programming, Uncertainty Reasoning and Machine Learning. This book includes definitions that circumscribe the area formed by extending Inductive Logic Programming to cases annotated with probability values. It investigates the approach of Learning from proofs and the issue of upgrading Fisher Kernels to Relational Fisher Kernels.Frontiers in artificial intelligence and applications.Dissertations in artificial intelligence.Frontiers in artificial intelligence and applications ;v. 148.Logic programmingUncertainty (Information theory)Machine learningMarkov processesLogic programming.Uncertainty (Information theory)Machine learning.Markov processes.Kersting Kristian1539425MiAaPQMiAaPQMiAaPQBOOK9910784254203321An inductive logic programming approach to statistical relational learning3790310UNINA