000			07673nam a22006255i 4500
001			978-3-642-04180-8
003			DE-He213
005			20240730183347.0
007			cr nn 008mamaa
008			100301s2009 gw | s |||| 0|eng d
020			_a9783642041808 _9978-3-642-04180-8
024	7		_a10.1007/978-3-642-04180-8 _2doi
050		4	_aTK5105.5-5105.9
072		7	_aUKN _2bicssc
072		7	_aCOM043000 _2bisacsh
072		7	_aUKN _2thema
082	0	4	_a004.6 _223
245	1	0	_aMachine Learning and Knowledge Discovery in Databases _h[electronic resource] : _bEuropean Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part I / _cedited by Wray Buntine, Marko Grobelnik, Dunja Mladenic, John Shawe-Taylor.
250			_a1st ed. 2009.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2009.
300			_aXXIX, 756 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v5781
505	0		_aInvited Talks (Abstracts) -- Theory-Practice Interplay in Machine Learning - Emerging Theoretical Challenges -- Are We There Yet? -- The Growing Semantic Web -- Privacy in Web Search Query Log Mining -- Highly Multilingual News Analysis Applications -- Machine Learning Journal Abstracts -- Combining Instance-Based Learning and Logistic Regression for Multilabel Classification -- On Structured Output Training: Hard Cases and an Efficient Alternative -- Sparse Kernel SVMs via Cutting-Plane Training -- Hybrid Least-Squares Algorithms for Approximate Policy Evaluation -- A Self-training Approach to Cost Sensitive Uncertainty Sampling -- Learning Multi-linear Representations of Distributions for Efficient Inference -- Cost-Sensitive Learning Based on Bregman Divergences -- Data Mining and Knowledge Discovery Journal Abstracts -- RTG: A Recursive Realistic Graph Generator Using Random Typing -- Taxonomy-Driven Lumping for Sequence Mining -- On Subgroup Discovery in Numerical Domains -- Harnessing the Strengths of Anytime Algorithms for Constant Data Streams -- Identifying the Components -- Two-Way Analysis of High-Dimensional Collinear Data -- A Fast Ensemble Pruning Algorithm Based on Pattern Mining Process -- Regular Papers -- Evaluation Measures for Multi-class Subgroup Discovery -- Empirical Study of Relational Learning Algorithms in the Phase Transition Framework -- Topic Significance Ranking of LDA Generative Models -- Communication-Efficient Classification in P2P Networks -- A Generalization of Forward-Backward Algorithm -- Mining Graph Evolution Rules -- Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks -- Adaptive XML Tree Classification on Evolving Data Streams -- A Condensed Representation of Itemsets for Analyzing Their Evolution over Time -- Non-redundant Subgroup Discovery Using a Closure System -- PLSI: The True Fisher Kernel and beyond -- Semi-supervised Document Clustering with Simultaneous Text Representation and Categorization -- One Graph Is Worth a ThousandLogs: Uncovering Hidden Structures in Massive System Event Logs -- Conference Mining via Generalized Topic Modeling -- Within-Network Classification Using Local Structure Similarity -- Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC) -- Kernel Polytope Faces Pursuit -- Soft Margin Trees -- Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs -- Margin and Radius Based Multiple Kernel Learning -- Inference and Validation of Networks -- Binary Decomposition Methods for Multipartite Ranking -- Leveraging Higher Order Dependencies between Features for Text Classification -- Syntactic Structural Kernels for Natural Language Interfaces to Databases -- Active and Semi-supervised Data Domain Description -- A Matrix Factorization Approach for Integrating Multiple Data Views -- Transductive Classification via Dual Regularization -- Stable and Accurate Feature Selection -- Efficient Sample Reuse in EM-Based Policy Search -- Applying Electromagnetic Field Theory Concepts to Clustering with Constraints -- An ?1 Regularization Framework for Optimal Rule Combination -- A Generic Approach to Topic Models -- Feature Selection by Transfer Learning with Linear Regularized Models -- Integrating Logical Reasoning and Probabilistic Chain Graphs -- Max-Margin Weight Learning for Markov Logic Networks -- Parameter-Free Hierarchical Co-clustering by n-Ary Splits -- Mining Peculiar Compositions of Frequent Substrings from Sparse Text Data Using Background Texts -- Minimum Free Energy Principle for Constraint-Based Learning Bayesian Networks -- Kernel-Based Copula Processes -- Compositional Models for Reinforcement Learning -- Feature Selection for Value Function Approximation Using Bayesian Model Selection -- Learning Preferences with Hidden Common Cause Relations -- Feature Selection for Density Level-Sets -- Efficient Multi-start Strategies for Local Search Algorithms -- Considering Unseen States as Impossible in Factored Reinforcement Learning -- Relevance Grounding for Planning in Relational Domains.
520			_aThis book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009. The 106 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 422 paper submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. 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. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
650		0	_aComputer networks . _931572
650		0	_aData mining. _93907
650		0	_aDatabase management. _93157
650		0	_aArtificial intelligence. _93407
650		0	_aInformation storage and retrieval systems. _922213
650	1	4	_aComputer Communication Networks. _9131674
650	2	4	_aData Mining and Knowledge Discovery. _9131675
650	2	4	_aDatabase Management. _93157
650	2	4	_aArtificial Intelligence. _93407
650	2	4	_aInformation Storage and Retrieval. _923927
700	1		_aBuntine, Wray. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9131676
700	1		_aGrobelnik, Marko. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9131677
700	1		_aMladenic, Dunja. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9131678
700	1		_aShawe-Taylor, John. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9131679
710	2		_aSpringerLink (Online service) _9131680
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783642041792
776	0	8	_iPrinted edition: _z9783642041815
830		0	_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v5781 _9131681
856	4	0	_uhttps://doi.org/10.1007/978-3-642-04180-8
912			_aZDB-2-SCS
912			_aZDB-2-SXCS
912			_aZDB-2-LNC
942			_cELN
999			_c91824 _d91824