001444702 000__ 04877cam\a2200625Ii\4500
001444702 001__ 1444702
001444702 003__ OCoLC
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001444702 020__ $$a9783030974541$$q(electronic bk.)
001444702 020__ $$a3030974545$$q(electronic bk.)
001444702 020__ $$z9783030974534
001444702 0247_ $$a10.1007/978-3-030-97454-1$$2doi
001444702 035__ $$aSP(OCoLC)1300781537
001444702 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCO$$dOCLCF$$dUKAHL$$dOCLCQ
001444702 049__ $$aISEA
001444702 050_4 $$aQA76.63$$b.I47 2021eb
001444702 08204 $$a005.1/15$$223
001444702 1112_ $$aILP (Conference)$$n(30th :$$d2021 :$$cOnline)
001444702 24510 $$aInductive logic programming :$$b30th International Conference, ILP 2021, Virtual event, October 25-27, 2021, Proceedings /$$cNikos Katzouris, Alexander Artikis (eds.).
001444702 2463_ $$aILP 2021
001444702 264_1 $$aCham, Switzerland :$$bSpringer,$$c2022.
001444702 300__ $$a1 online resource (x, 283 pages) :$$billustrations (some color).
001444702 336__ $$atext$$btxt$$2rdacontent
001444702 337__ $$acomputer$$bc$$2rdamedia
001444702 338__ $$aonline resource$$bcr$$2rdacarrier
001444702 4901_ $$aLecture notes in artificial intelligence
001444702 4901_ $$aLecture notes in computer science ;$$v13191
001444702 4901_ $$aLNCS sublibrary, SL 7, Artificial intelligence
001444702 500__ $$aIncludes author index.
001444702 5050_ $$aEmbedding Models for Knowledge Graphs Induced by Clusters of Relations and Background Knowledge -- Fanizzi Automatic Conjecturing of P-Recursions Using Lifted Inference -- Machine learning of microbial interactions using Abductive ILP and Hypothesis Frequency/Compression Estimation -- Answer-Set Programs for Reasoning about Counterfactual Interventions and Responsibility Scores for Classification -- Reyes Synthetic Datasets and Evaluation Tools for Inductive Neural Reasoning -- Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design -- Non-Parametric Learning of Embeddings for Relational Data using Gaifman Locality Theorem -- Ontology Graph Embeddings and ILP for Financial Forecasting -- Transfer learning for boosted relational dependency networks through genetic algorithm -- Online Learning of Logic Based Neural Network Structures -- Programmatic policy extraction by iterative local search -- Mapping across relational domains for transfer learning with word embeddings-based similarity -- A First Step Towards Even More Sparse Encodings of Probability Distributions -- Feature Learning by Least Generalization -- Learning Logic Programs Using Neural Networks by Exploiting Symbolic Invariance -- Learning and revising dynamic temporal theories in the full Discrete Event Calculus -- Human-like rule learning from images using one-shot hypothesis derivation -- Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits -- A Simulated Annealing Meta-heuristic for Concept Learning in Description Logics.
001444702 506__ $$aAccess limited to authorized users.
001444702 520__ $$aThis book constitutes the refereed conference proceedings of the 30th International Conference on Inductive Logic Programming, ILP 2032, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 papers and 3 short papers presented were carefully reviewed and selected from 19 submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data.
001444702 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed March 1, 2022).
001444702 650_0 $$aLogic programming$$vCongresses.
001444702 650_0 $$aInduction (Logic)$$vCongresses.
001444702 650_0 $$aMachine learning$$vCongresses.
001444702 650_6 $$aProgrammation logique$$vCongrès.
001444702 650_6 $$aInduction (Logique)$$vCongrès.
001444702 650_6 $$aApprentissage automatique$$vCongrès.
001444702 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001444702 655_0 $$aElectronic books.
001444702 7001_ $$aKatzouris, Nikos,$$eeditor.$$0(orcid)0000-0001-8804-470X$$1https://orcid.org/0000-0001-8804-470X
001444702 7001_ $$aArtikis, Alexander,$$eeditor.$$1https://orcid.org/0000-0001-6899-4599
001444702 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001444702 830_0 $$aLecture notes in computer science ;$$v13191.
001444702 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001444702 852__ $$bebk
001444702 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-97454-1$$zOnline Access$$91397441.1
001444702 909CO $$ooai:library.usi.edu:1444702$$pGLOBAL_SET
001444702 980__ $$aBIB
001444702 980__ $$aEBOOK
001444702 982__ $$aEbook
001444702 983__ $$aOnline
001444702 994__ $$a92$$bISE