## Advances in Intelligent Data Analysis VIII: 8th International Symposium on Intelligent Data Analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009, ProceedingsNiall M. Adams, Céline Robardet, Arno Siebes, Jean-Francois Boulicaut 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. |

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### Contents

Intelligent Data Analysis in the 21st Century | 1 |

Analyzing the Localization of Retail Stores with Complex Systems Tools | 10 |

Finding Distributional Shifts in Data Streams | 21 |

Exploiting Data Missingness in Bayesian Network Modeling | 35 |

Large Scale MDS Accounting for a Ridge Operator and Demographic Variables | 47 |

How to Control Clustering Results? Flexible Clustering Aggregation | 59 |

Compensation of Translational Displacement in Time Series Clustering Using Cross Correlation | 71 |

ContextBased Distance Learning for Categorical Data Clustering | 83 |

ZeroInflated Boosted Ensembles for Rare Event Counts | 225 |

Mining the Temporal Dimension of the Information Propagation | 237 |

Adaptive Learning from Evolving Data Streams | 249 |

An Application of Intelligent Data Analysis Techniques to a Large Software Engineering Dataset | 261 |

Which Distance for the Identification and the Differentiation of CellCycle Expressed Genes? | 273 |

OntologyDriven KDD Process Composition | 285 |

Mining Frequent Gradual Itemsets from Large Databases | 297 |

Selecting Computer Architectures by Means of ControlFlowGraph Mining | 309 |

Semisupervised Text Classification Using RBF Networks | 95 |

Improving kNN for Human Cancer Classification Using the Gene Expression Profiles | 107 |

A Novel Approach and Its Application to Breast Cancer Diagnosis | 119 |

Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases | 131 |

Leveraging Call Center Logs for Customer Behavior Prediction | 143 |

Condensed Representation of Sequential Patterns According to FrequencyBased Measures | 155 |

ARTBased Neural Networks for Multilabel Classification | 167 |

TwoWay Grouping by OneWay Topic Models | 178 |

Selecting and Weighting Data for Building Consensus Gene Regulatory Networks | 190 |

Incremental Bayesian Network Learning for Scalable Feature Selection | 202 |

Feature Extraction and Selection from Vibration Measurements for Structural Health Monitoring | 213 |

VisualizationDriven Structural and Statistical Analysis of Turbulent Flows | 321 |

Distributed Algorithm for Computing Formal Concepts Using MapReduce Framework | 333 |

MultiOptimisation Consensus Clustering | 345 |

Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences | 357 |

Measure of Similarity and Compactness in Competitive Space | 369 |

Bayesian Solutions to the Label Switching Problem | 381 |

Efficient Vertical Mining of Frequent Closures and Generators | 393 |

Isotonic Classification Trees | 405 |

417 | |

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accuracy algorithm applied approach attributes average Bayesian network behavior Berlin Heidelberg 2009 binary matrix classification coefficient compute correlation CVFDT data analysis Data Mining data streams database dataset decision tree defined denotes detection distance distribution documents Enron error estimates Euclidean distance evaluation example experiments feature selection Formal Concept Analysis formal concepts framework frequency-based measures frequent function gene expression gradual itemset graph graph mining Heidelberg IEEE instances iteration kernel labeled LNCS Machine Learning mapping Markov Markov blanket matrix method metric minsupport missing data mixture model MOCC multi-label Multidimensional Scaling Newsgroup nodes objects optimal pa-cases pair paper parameters performance prediction problem proposed random refactoring regression represents samples scalable Section sequences similarity solution space Springer statistical structure subgroups subset Table techniques trajectory tree tuples unlabeled data users values variables vector visualization WCBN weights