Machine Learning and Knowledge Discovery in Databases - neues Buch

EAN (ISBN-13): 9783642159398
Erscheinungsjahr: 2010
Herausgeber: Springer Berlin Heidelberg

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ISBN/EAN: 9783642159398

ISBN - alternative Schreibweisen:
978-3-642-15939-8
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: aristides, berlin, gioni, sebag
Titel des Buches: the machine seen, 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 Artificial Intelligence; Lecture Notes in Computer Science; Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part III
Verlag: Springer; Springer Berlin
632 Seiten
Erscheinungsjahr: 2010-08-18
Berlin; Heidelberg; DE
Sprache: Englisch
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
XXII, 632 p. 183 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.- Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations.- Unsupervised Trajectory Sampling.- Fast Extraction of Locally Optimal Patterns Based on Consistent Pattern Function Variations.- Large Margin Learning of Bayesian Classifiers Based on Gaussian Mixture Models.- Learning with Ensembles of Randomized Trees : New Insights.- Entropy and Margin Maximization for Structured Output Learning.- Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms.- Adapting Decision DAGs for Multipartite Ranking.- Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs.- Modeling Relations and Their Mentions without Labeled Text.- An Efficient and Scalable Algorithm for Local Bayesian Network Structure Discovery.- Selecting Information Diffusion Models over Social Networks for Behavioral Analysis.- Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach.- Online Structural Graph Clustering Using Frequent Subgraph Mining.- Large-Scale Support Vector Learning with Structural Kernels.- Synchronization Based Outlier Detection.- Laplacian Spectrum Learning.- k-Version-Space Multi-class Classification Based on k-Consistency Tests.- Complexity Bounds for Batch Active Learning in Classification.- Semi-supervised Projection Clustering with Transferred Centroid Regularization.- Permutation Testing Improves Bayesian Network Learning.- Example-dependent Basis Vector Selection for Kernel-Based Classifiers.- Surprising Patterns for the Call Duration Distribution of Mobile Phone Users.- Variational Bayesian Mixture of Robust CCA Models.- Adverse Drug Reaction Mining in Pharmacovigilance Data Using Formal Concept Analysis.- Topic Models Conditioned on Relations.- Shift-Invariant Grouped Multi-task Learning for Gaussian Processes.- Nonparametric Bayesian Clustering Ensembles.- Directed Graph Learning via High-Order Co-linkage Analysis.- Incorporating Domain Models into Bayesian Optimization for RL.- Efficient and Numerically Stable Sparse Learning.- Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes.- Many-to-Many Graph Matching: A Continuous Relaxation Approach.- Competitive Online Generalized Linear Regression under Square Loss.- Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning.- Fast, Effective Molecular Feature Mining by Local Optimization.- Demo Papers.- AnswerArt - Contextualized Question Answering.- Real-Time News Recommender System.- CET: A Tool for Creative Exploration of Graphs.- NewsGist: A Multilingual Statistical News Summarizer.- QUEST: Query Expansion Using Synonyms over Time.- Flu Detector - Tracking Epidemics on Twitter.- X-SDR: An Extensible Experimentation Suite for Dimensionality Reduction.- SOREX: Subspace Outlier Ranking Exploration Toolkit.- KDTA: Automated Knowledge-Driven Text Annotation.- Detecting Events in a Million New York Times Articles.- Experience STORIES: A Visual News Search and Summarization System.- Exploring Real Mobility Data with M-Atlas.
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