| 000 | 05379nam a22005895i 4500 | ||
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| 001 | 978-3-642-34156-4 | ||
| 003 | DE-He213 | ||
| 005 | 20140220083329.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 121026s2012 gw | s |||| 0|eng d | ||
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_a9783642341564 _9978-3-642-34156-4 |
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| 024 | 7 |
_a10.1007/978-3-642-34156-4 _2doi |
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| 050 | 4 | _aQA76.9.D3 | |
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_aUN _2bicssc |
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_aCOM021000 _2bisacsh |
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| 082 | 0 | 4 |
_a005.74 _223 |
| 100 | 1 |
_aHollmén, Jaakko. _eeditor. |
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| 245 | 1 | 0 |
_aAdvances in Intelligent Data Analysis XI _h[electronic resource] : _b11th International Symposium, IDA 2012, Helsinki, Finland, October 25-27, 2012. Proceedings / _cedited by Jaakko Hollmén, Frank Klawonn, Allan Tucker. |
| 264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2012. |
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| 300 |
_aXIV, 426 p. 136 illus. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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| 490 | 1 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v7619 |
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| 505 | 0 | _aIntelligent Data Analysis of Human Genetic Data -- Queries for Data Analysis -- Parallel Data Mining Revisited. Better, not Faster -- Weighting Features for Partition Around Medoids Using the Minkowski Metric -- On Initializations for the Minkowski Weighted K-Means -- A Skew-t-normal Multi-level Reduced-rank Functional PCA Model for the Analysis of Replicated Genomics Time Course Data -- Methodological Foundation for Sign Language 3D Motion Trajectory Analysis -- Assembly Detection in Continuous Neural Spike Train Data -- Online Techniques for Dealing with Concept Drift in Process Mining -- An Evolutionary Based Clustering Algorithm Applied to Data Compression for Industrial Systems -- Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns -- Discriminative Dimensionality Reduction Mappings -- Finding Interesting Contexts for Explaining Deviations in Bus Trip Duration Using Distribution Rules -- Curve Fitting for Short Time Series Data from High Throughput Experiments with Correction for Biological Variation -- MCut: A Thresholding Strategy for Multi-label Classification -- Improving Tag Recommendation Using Few Associations -- Identifying Anomalous Social Contexts from Mobile Proximity Data Using Binomial Mixture Models -- Constrained Clustering Using SAT -- Two-stage Approach for Electricity Consumption Forecasting in Public Buildings -- Online Predictive Model for Taxi Services -- Analysis of Noisy Biosignals for Musical Performance -- Information Theoretic Approach to Improve Performance of Networked Control Systems -- Learning Pattern Graphs for Multivariate Temporal Pattern Retrieval -- Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data -- Applying Piecewise Approximation in Perceptron Training of Conditional Random Fields -- Patch-based Data Analysis Using Linear-Projection Diffusion -- Dictionary Construction for Patch-to-Tensor Embedding -- Where Are We Going? Predicting the Evolution of Individuals -- Use of General Purpose GPU Programing to Enhance the Classification of Leukaemia Blast Cells in Blood Smear Images -- Intelligent Data Analysis by a Home-Use Human Monitoring Robot -- Sleep Musicalization: Automatic Music Composition from Sleep Measurements -- Engine Parameter Outlier Detection: Verification by Simulating PID Controllers Generated by Genetic Algorithm -- Unit Operational Pattern Analysis and Forecasting using EMD and SSA for Industrial Systems. | |
| 520 | _aThis book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Analysis, IDA 2012, held in Helsinki, Finland, in October 2012. The 32 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 88 submissions. All current aspects of intelligent data analysis are addressed, including intelligent support for modeling and analyzing data from complex, dynamical systems. The papers focus on novel applications of IDA techniques to, e.g., networked digital information systems; novel modes of data acquisition and the associated issues; robustness and scalability issues of intelligent data analysis techniques; and visualization and dissemination results. | ||
| 650 | 0 | _aComputer science. | |
| 650 | 0 | _aComputer software. | |
| 650 | 0 | _aDatabase management. | |
| 650 | 0 | _aData mining. | |
| 650 | 0 | _aInformation storage and retrieval systems. | |
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 1 | 4 | _aComputer Science. |
| 650 | 2 | 4 | _aDatabase Management. |
| 650 | 2 | 4 | _aInformation Systems Applications (incl. Internet). |
| 650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
| 650 | 2 | 4 | _aInformation Storage and Retrieval. |
| 650 | 2 | 4 | _aAlgorithm Analysis and Problem Complexity. |
| 650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
| 700 | 1 |
_aKlawonn, Frank. _eeditor. |
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| 700 | 1 |
_aTucker, Allan. _eeditor. |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783642341557 |
| 830 | 0 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v7619 |
|
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-34156-4 |
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| 912 | _aZDB-2-LNC | ||
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