LEADER 06716nam 22008055 450 001 996466569903316 005 20200704232646.0 010 $a1-280-38918-4 010 $a9786613567109 010 $a3-642-15880-3 024 7 $a10.1007/978-3-642-15880-3 035 $a(CKB)2670000000036420 035 $a(SSID)ssj0000446611 035 $a(PQKBManifestationID)11281734 035 $a(PQKBTitleCode)TC0000446611 035 $a(PQKBWorkID)10496414 035 $a(PQKB)11446002 035 $a(DE-He213)978-3-642-15880-3 035 $a(MiAaPQ)EBC3065670 035 $a(PPN)149018126 035 $a(EXLCZ)992670000000036420 100 $a20100817d2010 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aMachine Learning and Knowledge Discovery in Databases$b[electronic resource] $eEuropean Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part I /$fedited by José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag 205 $a1st ed. 2010. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2010. 215 $a1 online resource (XXX, 620 p. 175 illus.) 225 1 $aLecture Notes in Artificial Intelligence ;$v6321 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-15879-X 320 $aIncludes bibliographical references and index. 327 $aInvited Talks (Abstracts) -- Mining Billion-Node Graphs: Patterns, Generators and Tools -- Structure Is Informative: On Mining Structured Information Networks -- Intelligent Interaction with the Real World -- Mining Experimental Data for Dynamical Invariants - From Cognitive Robotics to Computational Biology -- Hierarchical Learning Machines and Neuroscience of Visual Cortex -- Formal Theory of Fun and Creativity -- Regular Papers -- Porting Decision Tree Algorithms to Multicore Using FastFlow -- On Classifying Drifting Concepts in P2P Networks -- A Unified Approach to Active Dual Supervision for Labeling Features and Examples -- Vector Field Learning via Spectral Filtering -- Weighted Symbols-Based Edit Distance for String-Structured Image Classification -- A Concise Representation of Association Rules Using Minimal Predictive Rules -- Euclidean Distances, Soft and Spectral Clustering on Weighted Graphs -- Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks -- Leveraging Bagging for Evolving Data Streams -- ITCH: Information-Theoretic Cluster Hierarchies -- Coniunge et Impera: Multiple-Graph Mining for Query-Log Analysis -- Process Mining Meets Abstract Interpretation -- Smarter Sampling in Model-Based Bayesian Reinforcement Learning -- Predicting Partial Orders: Ranking with Abstention -- Predictive Distribution Matching SVM for Multi-domain Learning -- Kantorovich Distances between Rankings with Applications to Rank Aggregation -- Characteristic Kernels on Structured Domains Excel in Robotics and Human Action Recognition -- Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss -- Clustering Vessel Trajectories with Alignment Kernels under Trajectory Compression -- Adaptive Bases for Reinforcement Learning -- Constructing Nonlinear Discriminants from Multiple Data Views -- Learning Algorithms for Link Prediction Based on Chance Constraints -- Sparse Unsupervised Dimensionality Reduction Algorithms -- Asking Generalized Queries to Ambiguous Oracle -- Analysis of Large Multi-modal Social Networks: Patterns and a Generator -- A Cluster-Level Semi-supervision Model for Interactive Clustering -- Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs -- Induction of Concepts in Web Ontologies through Terminological Decision Trees -- Classification with Sums of Separable Functions -- Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information -- Bagging for Biclustering: Application to Microarray Data -- Hub Gene Selection Methods for the Reconstruction of Transcription Networks -- Expectation Propagation for Bayesian Multi-task Feature Selection -- Graphical Multi-way Models -- Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval -- Graph Regularized Transductive Classification on Heterogeneous Information Networks -- Temporal Maximum Margin Markov Network -- Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration. 410 0$aLecture Notes in Artificial Intelligence ;$v6321 606 $aArtificial intelligence 606 $aData structures (Computer science) 606 $aApplication software 606 $aInformation storage and retrieval 606 $aDatabase management 606 $aData mining 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aData Structures and Information Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/I15009 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 615 0$aArtificial intelligence. 615 0$aData structures (Computer science). 615 0$aApplication software. 615 0$aInformation storage and retrieval. 615 0$aDatabase management. 615 0$aData mining. 615 14$aArtificial Intelligence. 615 24$aData Structures and Information Theory. 615 24$aInformation Systems Applications (incl. Internet). 615 24$aInformation Storage and Retrieval. 615 24$aDatabase Management. 615 24$aData Mining and Knowledge Discovery. 676 $a006.3 702 $aBalcázar$b José L$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBonchi$b Francesco$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGionis$b Aristides$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSebag$b Michèle$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996466569903316 996 $aMachine Learning and Knowledge Discovery in Databases$9773712 997 $aUNISA