05110nam 22007695 450 99646559020331620200630023352.03-642-33486-510.1007/978-3-642-33486-3(CKB)3400000000086228(SSID)ssj0000767549(PQKBManifestationID)11436213(PQKBTitleCode)TC0000767549(PQKBWorkID)10741674(PQKB)11360773(DE-He213)978-3-642-33486-3(MiAaPQ)EBC3070970(PPN)168324636(EXLCZ)99340000000008622820120910d2012 u| 0engurnn#008mamaatxtccrMachine Learning and Knowledge Discovery in Databases[electronic resource] European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II /edited by Peter A. Flach, Tijl De Bie, Nello Cristianini1st ed. 2012.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2012.1 online resource (XXVI, 867 p. 245 illus.)Lecture Notes in Artificial Intelligence ;7524Bibliographic Level Mode of Issuance: Monograph3-642-33485-7 Privacy and security -- rankings and recommendations -- reinforcement learning and planning -- rule mining and subgroup discovery -- semi-supervised and transductive learning -- sensor data -- sequence and string mining -- social network mining -- spatial and geographical data mining -- statistical methods and evaluation -- time series and temporal data mining -- transfer learning.This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012. The 105 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 443 submissions. The final sections of the proceedings are devoted to Demo and Nectar papers. The Demo track includes 10 papers (from 19 submissions) and the Nectar track includes 4 papers (from 14 submissions). The papers grouped in topical sections on association rules and frequent patterns; Bayesian learning and graphical models; classification; dimensionality reduction, feature selection and extraction; distance-based methods and kernels; ensemble methods; graph and tree mining; large-scale, distributed and parallel mining and learning; multi-relational mining and learning; multi-task learning; natural language processing; online learning and data streams; privacy and security; rankings and recommendations; reinforcement learning and planning; rule mining and subgroup discovery; semi-supervised and transductive learning; sensor data; sequence and string mining; social network mining; spatial and geographical data mining; statistical methods and evaluation; time series and temporal data mining; and transfer learning.Lecture Notes in Artificial Intelligence ;7524Data miningArtificial intelligencePattern recognitionComputer science—MathematicsMathematical statisticsInformation storage and retrievalData Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XDiscrete Mathematics in Computer Sciencehttps://scigraph.springernature.com/ontologies/product-market-codes/I17028Probability and Statistics in Computer Sciencehttps://scigraph.springernature.com/ontologies/product-market-codes/I17036Information Storage and Retrievalhttps://scigraph.springernature.com/ontologies/product-market-codes/I18032Data mining.Artificial intelligence.Pattern recognition.Computer science—Mathematics.Mathematical statistics.Information storage and retrieval.Data Mining and Knowledge Discovery.Artificial Intelligence.Pattern Recognition.Discrete Mathematics in Computer Science.Probability and Statistics in Computer Science.Information Storage and Retrieval.006.312Flach Peter Aedthttp://id.loc.gov/vocabulary/relators/edtDe Bie Tijledthttp://id.loc.gov/vocabulary/relators/edtCristianini Nelloedthttp://id.loc.gov/vocabulary/relators/edtBOOK996465590203316Machine Learning and Knowledge Discovery in Databases773712UNISA