LEADER 06324nam 22008775 450 001 996465760203316 005 20200704100910.0 010 $a3-642-03915-4 024 7 $a10.1007/978-3-642-03915-7 035 $a(CKB)1000000000772846 035 $a(SSID)ssj0000316001 035 $a(PQKBManifestationID)11229635 035 $a(PQKBTitleCode)TC0000316001 035 $a(PQKBWorkID)10263059 035 $a(PQKB)10300352 035 $a(DE-He213)978-3-642-03915-7 035 $a(MiAaPQ)EBC3064481 035 $a(PPN)139955224 035 $a(EXLCZ)991000000000772846 100 $a20100301d2009 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in Intelligent Data Analysis VIII$b[electronic resource] $e8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009, Proceedings /$fedited by Niall M. Adams, Céline Robardet, Arno Siebes, Jean-Francois Boulicaut 205 $a1st ed. 2009. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2009. 215 $a1 online resource (XIII, 418 p.) 225 1 $aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v5772 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-03914-6 320 $aIncludes bibliographical references and index. 327 $aInvited Papers -- Intelligent Data Analysis in the 21st Century -- Analyzing the Localization of Retail Stores with Complex Systems Tools -- Selected Contributions 1 (Long Talks) -- Change (Detection) You Can Believe in: Finding Distributional Shifts in Data Streams -- Exploiting Data Missingness in Bayesian Network Modeling -- DEMScale: Large Scale MDS Accounting for a Ridge Operator and Demographic Variables -- How to Control Clustering Results? Flexible Clustering Aggregation -- Compensation of Translational Displacement in Time Series Clustering Using Cross Correlation -- Context-Based Distance Learning for Categorical Data Clustering -- Semi-supervised Text Classification Using RBF Networks -- Improving k-NN for Human Cancer Classification Using the Gene Expression Profiles -- Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis -- Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases -- Leveraging Call Center Logs for Customer Behavior Prediction -- Condensed Representation of Sequential Patterns According to Frequency-Based Measures -- ART-Based Neural Networks for Multi-label Classification -- Two-Way Grouping by One-Way Topic Models -- Selecting and Weighting Data for Building Consensus Gene Regulatory Networks -- Incremental Bayesian Network Learning for Scalable Feature Selection -- Feature Extraction and Selection from Vibration Measurements for Structural Health Monitoring -- Zero-Inflated Boosted Ensembles for Rare Event Counts -- Selected Contributions 2 (Short Talks) -- Mining the Temporal Dimension of the Information Propagation -- Adaptive Learning from Evolving Data Streams -- An Application of Intelligent Data Analysis Techniques to a Large Software Engineering Dataset -- Which Distance for the Identification and the Differentiation of Cell-Cycle Expressed Genes? -- Ontology-Driven KDD Process Composition -- Mining Frequent Gradual Itemsets from Large Databases -- Selecting Computer Architectures by Means of Control-Flow-Graph Mining -- Visualization-Driven Structural and Statistical Analysis of Turbulent Flows -- Distributed Algorithm for Computing Formal Concepts Using Map-Reduce Framework -- Multi-Optimisation Consensus Clustering -- Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences -- Measure of Similarity and Compactness in Competitive Space -- Bayesian Solutions to the Label Switching Problem -- Efficient Vertical Mining of Frequent Closures and Generators -- Isotonic Classification Trees. 410 0$aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v5772 606 $aComputers 606 $aInformation storage and retrieval 606 $aData mining 606 $aPattern recognition 606 $aData structures (Computer science) 606 $aInformation technology 606 $aBusiness?Data processing 606 $aTheory of Computation$3https://scigraph.springernature.com/ontologies/product-market-codes/I16005 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aData Structures$3https://scigraph.springernature.com/ontologies/product-market-codes/I15017 606 $aIT in Business$3https://scigraph.springernature.com/ontologies/product-market-codes/522000 608 $aKongress.$2swd 608 $aLyon (2008)$2swd 615 0$aComputers. 615 0$aInformation storage and retrieval. 615 0$aData mining. 615 0$aPattern recognition. 615 0$aData structures (Computer science). 615 0$aInformation technology. 615 0$aBusiness?Data processing. 615 14$aTheory of Computation. 615 24$aInformation Storage and Retrieval. 615 24$aData Mining and Knowledge Discovery. 615 24$aPattern Recognition. 615 24$aData Structures. 615 24$aIT in Business. 676 $a006.31222gerDNB 686 $aDAT 703f$2stub 686 $aMAT 620f$2stub 686 $aSS 4800$2rvk 702 $aAdams$b Niall M$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRobardet$b Céline$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSiebes$b Arno$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBoulicaut$b Jean-Francois$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aInternational Symposium on Intelligent Data Analysis 906 $aBOOK 912 $a996465760203316 996 $aAdvances in Intelligent Data Analysis VIII$9773693 997 $aUNISA