Discovery Science 12th International Conference, DS 2009, Porto, Portugal, October 3-5, 2009
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Sprache:Englisch
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Verlag:Springer Berlin
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49,99 €
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
05.10.2009
Herausgeber
João Gama + weitereVerlag
Springer BerlinSeitenzahl
474
Maße (L/B/H)
23,5/15,5/2,7 cm
Gewicht
739 g
Auflage
2009
Sprache
Englisch
ISBN
978-3-642-04746-6
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.
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