Discovery science : 12th international conference, DS 2009, Porto, Portugal, October 3-5, 2009 : proceedings / / Joao Gama ... [et al.] (eds.)

• Pubblicazione: Berlin ; ; New York, : Springer, c2009
• Edizione: 1st ed. 2009.
• Descrizione fisica: 1 online resource (XIII, 474 p.)
• Disciplina: 006.3
• Soggetto topico: Science - Philosophy; Discoveries in science; Research - Automation; Research - Data processing
• Altri autori: GamaJoao
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Inference and Learning in Planning (Extended Abstract) -- Mining Heterogeneous Information Networks by Exploring the Power of Links -- Learning on the Web -- Learning and Domain Adaptation -- The Two Faces of Active Learning -- An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting -- Detecting New Kinds of Patient Safety Incidents -- Using Data Mining for Wine Quality Assessment -- MICCLLR: Multiple-Instance Learning Using Class Conditional Log Likelihood Ratio -- On the Complexity of Constraint-Based Theory Extraction -- Algorithm and Feature Selection for VegOut: A Vegetation Condition Prediction Tool -- Regression Trees from Data Streams with Drift Detection -- Mining Frequent Bipartite Episode from Event Sequences -- CHRONICLE: A Two-Stage Density-Based Clustering Algorithm for Dynamic Networks -- Learning Large Margin First Order Decision Lists for Multi-Class Classification -- Centrality Measures from Complex Networks in Active Learning -- Player Modeling for Intelligent Difficulty Adjustment -- Unsupervised Fuzzy Clustering for the Segmentation and Annotation of Upwelling Regions in Sea Surface Temperature Images -- Discovering the Structures of Open Source Programs from Their Developer Mailing Lists -- A Comparison of Community Detection Algorithms on Artificial Networks -- Towards an Ontology of Data Mining Investigations -- OMFP: An Approach for Online Mass Flow Prediction in CFB Boilers -- C-DenStream: Using Domain Knowledge on a Data Stream -- Discovering Influential Nodes for SIS Models in Social Networks -- An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules -- Precision and Recall for Regression -- Mining Local Correlation Patterns in Sets of Sequences -- Subspace Discovery for Promotion: A Cell Clustering Approach -- Contrasting Sequence Groups by Emerging Sequences -- A Sliding Window Algorithm for Relational Frequent Patterns Mining from Data Streams -- A Hybrid Collaborative Filtering System for Contextual Recommendations in Social Networks -- Linear Programming Boosting by Column and Row Generation -- Discovering Abstract Concepts to Aid Cross-Map Transfer for a Learning Agent -- A Dialectic Approach to Problem-Solving -- Gene Functional Annotation with Dynamic Hierarchical Classification Guided by Orthologs -- Stream Clustering of Growing Objects -- Finding the k-Most Abnormal Subgraphs from a Single Graph -- Latent Topic Extraction from Relational Table for Record Matching -- Computing a Comprehensible Model for Spam Filtering -- Better Decomposition Heuristics for the Maximum-Weight Connected Graph Problem Using Betweenness Centrality.
• Altri titoli varianti: DS 2009
• Titolo autorizzato: Discovery science
• ISBN: 3-642-04747-5
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910483631503321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture notes in computer science. . -Lecture notes in artificial intelligence.; Lecture notes in computer science ; ; 5808.