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Machine Learning and Knowledge Discovery in Databases (Paperback) - Taschenbuch

2010, ISBN: 364215882X

[EAN: 9783642158827], Neubuch, [PU: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin], Paperback. The European Conference on Machine Learning and Principles and Practice of Kno… Mehr…

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Machine Learning and Knowledge Discovery in Databases (Paperback) - Taschenbuch

2010, ISBN: 364215882X

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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 201 - neues Buch

2010

ISBN: 9783642158827

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2010, was held in Barcelona, September 20-24, 2010, consolidating th… Mehr…

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2010, ISBN: 9783642158827

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José L. Balcázar; Francesco Bonchi; Aristides Gionis; Michèle Sebag:
Machine Learning and Knowledge Discovery in Databases - Taschenbuch

2010, ISBN: 9783642158827

European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part II, Buch, Softcover, [PU: Springer Berlin], Springer Berlin, 2010

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Details zum Buch
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 201

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2010, held in Barcelona, Spain, in September 2010. The 120 revised full papers presented in three volumes, together with 12 demos (out of 24 submitted demos), were carefully reviewed and selected from 658 paper submissions. In addition, 7 ML and 7 DM papers were distinguished by the program chairs on the basis of their exceptional scientific quality and high impact on the field. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. A topic widely explored from both ML and DM perspectives was graphs, with motivations ranging from molecular chemistry to social networks.

Detailangaben zum Buch - Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 201


EAN (ISBN-13): 9783642158827
ISBN (ISBN-10): 364215882X
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2010
Herausgeber: Springer Berlin
518 Seiten
Gewicht: 0,750 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2007-10-25T09:09:30+02:00 (Vienna)
Detailseite zuletzt geändert am 2022-02-05T10:56:43+01:00 (Vienna)
ISBN/EAN: 9783642158827

ISBN - alternative Schreibweisen:
3-642-15882-X, 978-3-642-15882-7


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: 2010-09-13
Berlin; Heidelberg; DE
Gewicht: 0,808 kg
Sprache: Englisch
96,29 € (DE)
98,99 € (AT)
120,12 CHF (CH)
POD
XXI, 518 p. 145 illus.

BC; Book; Hardcover, Softcover / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Informatik; 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; Information Systems Applications (incl. Internet); Information Storage and Retrieval; Database Management; Data Mining and Knowledge Discovery; 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; EA

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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