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Advances in Intelligent Data Analysis VIII: 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009, Proceedings 2009 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 418 pages, kõrgus x laius: 235x155 mm, kaal: 664 g, XIII, 418 p., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 5772
  • Ilmumisaeg: 17-Aug-2009
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642039146
  • ISBN-13: 9783642039140
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Advances in Intelligent Data Analysis VIII: 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009, Proceedings 2009 ed.Suurem pilt
  • Formaat: Paperback / softback, 418 pages, kõrgus x laius: 235x155 mm, kaal: 664 g, XIII, 418 p., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 5772
  • Ilmumisaeg: 17-Aug-2009
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642039146
  • ISBN-13: 9783642039140
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783642039140.html
Märksõnad:
The general theme of the Intelligent Data Analysis (IDA) Symposia is the - telligent use of computers in complex data analysis problems. The ?eld has matured su ciently that some re-considerationof our objectives was required in order to retain the distinctiveness of IDA. Thus, in addition to the more tra- tional algorithm- and application-oriented submissions, we sought submissions that speci cally focus on aspects of the data analysis process. For example, - teractive tools to guide and support data analysis in complex scenarios. With the increasingavailabilityofautomaticallycollecteddata,toolsthatintelligently support and assist human analysts are becoming important. IDA-09, the 8th International Symposium on Intelligent Data Analysis, took place in Lyon from August 31 to September 2, 2009. The invited speakers were PaulCohen(UniversityofArizona,USA)andPabloJensen(ENSLyon,France). The meeting received more than 80 submissions. The Programme Committee selected 33 submissions for publication: 18 for full oral presentation, and 15 for poster and short oralpresentation. Eachcontribution was evaluated by three expertsandhas beenallocated12pagesintheproceedings.Theacceptedpapers cover a broad range of topics and applications, and include contributions on the re? ned focus of IDA.
Invited 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.