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001			298953
003			MX-SnUAN
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007			cr nn 008mamaa
008			150903s2008 gw | o |||| 0|eng d
020			_a9783540884118 _99783540884118
024	7		_a10.1007/9783540884118 _2doi
035			_avtls000352361
039		9	_a201509030938 _bVLOAD _c201405060304 _dVLOAD _y201402171159 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQ334-342
100	1		_aJean-Fran, Jean-François. _eeditor. _9335602
245	1	0	_aDiscovery Science : _b11th International Conference, DS 2008, Budapest, Hungary, October 13-16, 2008. Proceedings / _cedited by Jean-François Jean-Fran, Michael R. Berthold, Tamás Horváth.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2008.
300			_axii, 348 páginas 96 ilustraciones _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aLecture Notes in Computer Science, _x0302-9743 ; _v5255
500			_aSpringer eBooks
505	0		_aInvited Papers -- On Iterative Algorithms with an Information Geometry Background -- Visual Analytics: Combining Automated Discovery with Interactive Visualizations -- Some Mathematics Behind Graph Property Testing -- Finding Total and Partial Orders from Data for Seriation -- Computational Models of Neural Representations in the Human Brain -- Learning -- Unsupervised Classifier Selection Based on Two-Sample Test -- An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics -- Learning Model Trees from Data Streams -- Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees -- Ensemble-Trees: Leveraging Ensemble Power Inside Decision Trees -- A Comparison between Neural Network Methods for Learning Aggregate Functions -- Feature Selection -- Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns -- Feature Selection in Taxonomies with Applications to Paleontology -- Associations -- Deduction Schemes for Association Rules -- Constructing Iceberg Lattices from Frequent Closures Using Generators -- Discovery Processes -- Learning from Each Other -- Comparative Evaluation of Two Systems for the Visual Navigation of Encyclopedia Knowledge Spaces -- A Framework for Knowledge Discovery in a Society of Agents -- Learning and Chemistry -- Active Learning for High Throughput Screening -- An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules -- Mining Intervals of Graphs to Extract Characteristic Reaction Patterns -- Clustering -- Refining Pairwise Similarity Matrix for Cluster Ensemble Problem with Cluster Relations -- Input Noise Robustness and Sensitivity Analysis to Improve Large Datasets Clustering by Using the GRID -- An Integrated Graph and Probability Based Clustering Framework for Sequential Data -- Cluster Analysis in Remote Sensing Spectral Imagery through Graph Representation and Advanced SOM Visualization -- Structured Data -- Mining Unordered Distance-Constrained Embedded Subtrees -- Finding Frequent Patterns from Compressed Tree-Structured Data -- A Modeling Approach Using Multiple Graphs for Semi-Supervised Learning -- Text Analysis -- String Kernels Based on Variable-Length-Don’t-Care Patterns -- Unsupervised Spam Detection by Document Complexity Estimation -- A Probabilistic Neighbourhood Translation Approach for Non-standard Text Categorisation.
520			_aThis book constitutes the refereed proceedings of the 11th International Conference on Discovery Science, DS 2008, held in Budapest, Hungary, in October 2008, co-located with the 19th International Conference on Algorithmic Learning Theory, ALT 2008. The 26 revised long papers presented together with 5 invited papers were carefully reviewed and selected from 58 submissions. The papers address all current issues in the area of development and analysis of methods for intelligent data analysis, knowledge discovery and machine learning, as well as their application to scientific knowledge discovery. The papers are organized in topical sections on learning, feature selection, associations, discovery processes, learning and chemistry, clustering, structured data, and text analysis.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aBerthold, Michael R. _eeditor. _9322267
700	1		_aHorváth, Tamás. _eeditor. _9335603
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783540884101
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-88411-8 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c298953 _d298953