Machine Learning and Knowledge Discovery in Databases - neues Buch

EAN (ISBN-13): 9783642158834
Erscheinungsjahr: 2010
Herausgeber: Springer Berlin Heidelberg

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ISBN/EAN: 9783642158834

ISBN - alternative Schreibweisen:
978-3-642-15883-4
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: aristides, berlin, gioni, sebag
Titel des Buches: machine learning, knowledge discovery databases

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Daten vom Verlag:

Autor/in: José L. Balcázar; Francesco Bonchi; Aristides Gionis; Michèle Sebag
Titel: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part II
Verlag: Springer; Springer Berlin
518 Seiten
Erscheinungsjahr: 2010-08-17
Berlin; Heidelberg; DE
Sprache: Englisch
53,49 € (DE)
55,00 € (AT)
59,00 CHF (CH)
Available
XXI, 518 p. 145 illus.

EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; bio-informatics; classification; clustering; data analysis; data mining; databases; dimensionality reduction; graph mining; information retrieval; knowledge; knowledge discovery; learning; machine learning; semantic web; social networks; C; Artificial Intelligence; Data Structures and Information Theory; Computer and Information Systems Applications; Information Storage and Retrieval; Database Management; Data Mining and Knowledge Discovery; Computer Science; Algorithmen und Datenstrukturen; Informationstheorie; Angewandte Informatik; Informationsrückgewinnung, Information Retrieval; Data Warehousing; Datenbanken; Data Mining; Wissensbasierte Systeme, Expertensysteme; BC

Regular Papers.- Bayesian Knowledge Corroboration with Logical Rules and User Feedback.- Learning an Affine Transformation for Non-linear Dimensionality Reduction.- NDPMine: Efficiently Mining Discriminative Numerical Features for Pattern-Based Classification.- Hidden Conditional Ordinal Random Fields for Sequence Classification.- A Unifying View of Multiple Kernel Learning.- Evolutionary Dynamics of Regret Minimization.- Recognition of Instrument Timbres in Real Polytimbral Audio Recordings.- Finding Critical Nodes for Inhibiting Diffusion of Complex Contagions in Social Networks.- Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction.- Online Knowledge-Based Support Vector Machines.- Learning with Randomized Majority Votes.- Exploration in Relational Worlds.- Efficient Confident Search in Large Review Corpora.- Learning to Tag from Open Vocabulary Labels.- A Robustness Measure of Association Rules.- Automatic Model Adaptation for Complex Structured Domains.- Collective Traffic Forecasting.- On Detecting Clustered Anomalies Using SCiForest.- Constrained Parameter Estimation for Semi-supervised Learning: The Case of the Nearest Mean Classifier.- Online Learning in Adversarial Lipschitz Environments.- Summarising Data by Clustering Items.- Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space.- Latent Structure Pattern Mining.- First-Order Bayes-Ball.- Learning from Demonstration Using MDP Induced Metrics.- Demand-Driven Tag Recommendation.- Solving Structured Sparsity Regularization with Proximal Methods.- Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models.- Improved MinMax Cut Graph Clustering with Nonnegative Relaxation.- Integrating Constraint Programming and Itemset Mining.- Topic Modeling for Personalized Recommendation of Volatile Items.- Conditional Ranking on Relational Data.
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