06716nam 22008055 450 99646656990331620200704232646.01-280-38918-497866135671093-642-15880-310.1007/978-3-642-15880-3(CKB)2670000000036420(SSID)ssj0000446611(PQKBManifestationID)11281734(PQKBTitleCode)TC0000446611(PQKBWorkID)10496414(PQKB)11446002(DE-He213)978-3-642-15880-3(MiAaPQ)EBC3065670(PPN)149018126(EXLCZ)99267000000003642020100817d2010 u| 0engurnn|008mamaatxtccrMachine Learning and Knowledge Discovery in Databases[electronic resource] European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part I /edited by José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag1st ed. 2010.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2010.1 online resource (XXX, 620 p. 175 illus.) Lecture Notes in Artificial Intelligence ;6321Bibliographic Level Mode of Issuance: Monograph3-642-15879-X Includes bibliographical references and index.Invited 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.Lecture Notes in Artificial Intelligence ;6321Artificial intelligenceData structures (Computer science)Application softwareInformation storage and retrievalDatabase managementData miningArtificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Data Structures and Information Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/I15009Information Systems Applications (incl. Internet)https://scigraph.springernature.com/ontologies/product-market-codes/I18040Information Storage and Retrievalhttps://scigraph.springernature.com/ontologies/product-market-codes/I18032Database Managementhttps://scigraph.springernature.com/ontologies/product-market-codes/I18024Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Artificial intelligence.Data structures (Computer science).Application software.Information storage and retrieval.Database management.Data mining.Artificial Intelligence.Data Structures and Information Theory.Information Systems Applications (incl. Internet).Information Storage and Retrieval.Database Management.Data Mining and Knowledge Discovery.006.3Balcázar José Ledthttp://id.loc.gov/vocabulary/relators/edtBonchi Francescoedthttp://id.loc.gov/vocabulary/relators/edtGionis Aristidesedthttp://id.loc.gov/vocabulary/relators/edtSebag Michèleedthttp://id.loc.gov/vocabulary/relators/edtBOOK996466569903316Machine Learning and Knowledge Discovery in Databases773712UNISA