Machine Learning and Data Mining in Pattern Recognition

Third International Conference, MLDM 2003, Leipzig, Germany, July 5-7, 2003, Proceedings

By: Petra Perner (Editor), Azriel Rosenfeld (Editor)

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TheInternationalConferenceonMachineLearningandDataMining(MLDM)is the third meeting in a series of biennial events, which started in 1999, organized by the Institute of Computer Vision and Applied Computer Sciences (IBaI) in Leipzig. MLDM began as a workshop and is now a conference, and has brought the topic of machine learning and data mining to the attention of the research community. Seventy-?ve papers were submitted to the conference this year. The program committeeworkedhardtoselectthemostprogressiveresearchinafairandc- petent review process which led to the acceptance of 33 papers for presentation at the conference. The 33 papers in these proceedings cover a wide variety of topics related to machine learning and data mining. The two invited talks deal with learning in case-based reasoning and with mining for structural data. The contributed papers can be grouped into nine areas: support vector machines; pattern dis- very; decision trees; clustering; classi?cation and retrieval; case-based reasoning; Bayesian models and methods; association rules; and applications. We would like to express our appreciation to the reviewers for their precise andhighlyprofessionalwork.WearegratefultotheGermanScienceFoundation for its support of the Eastern European researchers. We appreciate the help and understanding of the editorial sta? at Springer Verlag, and in particular Alfred Hofmann,whosupportedthepublicationoftheseproceedingsintheLNAIseries. Last, but not least, we wish to thank all the speakers and participants who contributed to the success of the conference.

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Non-Fiction Computing & I.T.Computer Science Mathematical Theory of Computation Databases Data Mining Medicine Medicine in General Artificial Intelligence Machine Learning Mathematics Mathematical Foundation

Mathematical Logic Graphical & Digital Media Applications Computer Vision Pattern Recognition

Introspective Learning to Build Case-Based Reasoning (CBR) Knowledge Containers	p. 1
Graph-Based Tools for Data Mining and Machine Learning	p. 7
Simplification Methods for Model Trees with Regression and Splitting Nodes	p. 20
Learning Multi-label Alternating Decision Trees from Texts and Data	p. 35
Khiops: A Discretization Method of Continuous Attributes with Guaranteed Resistance to Noise	p. 50
On the Size of a Classification Tree	p. 65
A Comparative Analysis of Clustering Algorithms Applied to Load Profiling	p. 73
Similarity-Based Clustering of Sequences Using Hidden Markov Models	p. 86
A Fast Parallel Optimization for Training Support Vector Machine	p. 96
A ROC-Based Reject Rule for Support Vector Machines	p. 106
Remembering Similitude Terms in CBR	p. 121
Authoring Cases from Free-Text Maintenance Data	p. 131
Classification Boundary Approximation by Using Combination of Training Steps for Real-Time Image Segmentation	p. 141
Simple Mimetic Classifiers	p. 156
Novel Mixtures Based on the Dirichlet Distribution: Application to Data and Image Classification	p. 172
Estimating a Quality of Decision Function by Empirical Risk	p. 182
Efficient Locally Linear Embeddings of Imperfect Manifolds	p. 188
Dissimilarity Representation of Images for Relevance Feedback in Content-Based Image Retrieval	p. 202
A Rule-Based Scheme for Filtering Examples from Majority Class in an Imbalanced Training Set	p. 215
Coevolutionary Feature Learning for Object Recognition	p. 224
Generalization of Pattern-Growth Methods for Sequential Pattern Mining with Gap Constraints	p. 239
Discover Motifs in Multi-dimensional Time-Series Using the Principal Component Analysis and the MDL Principle	p. 252
Optimizing Financial Portfolios from the Perspective of Mining Temporal Structures of Stock Returns	p. 266
Visualizing Sequences of Texts Using Collocational Networks	p. 276
Complexity Analysis of Depth First and FP-Growth Implementations of APRIORI	p. 284
GO-SPADE: Mining Sequential Patterns over Datasets with Consecutive Repetitions	p. 293
Using Test Plans for Bayesian Modeling	p. 307
Using Bayesian Networks to Analyze Medical Data	p. 317
A Belief Networks-Based Generative Model for Structured Documents. An Application to the XML Categorization	p. 328
Neural Self-Organization Using Graphs	p. 343
Integrating Fuzziness with OLAP Association Rules Mining	p. 353
Discovering Association Patterns Based on Mutual Information	p. 369
Connectionist Probability Estimators in HMM Arabic Speech Recognition Using Fuzzy Logic	p. 379
Shape Recovery from an Unorganized Image Sequence	p. 389
A Learning Autonomous Driver System on the Basis of Image Classification and Evolutional Learning	p. 400
Detecting the Boundary Curve of Planar Random Point Set	p. 413
A Machine Learning Model for Information Retrieval with Structured Documents	p. 425
Author Index	p. 439
Table of Contents provided by Blackwell. All Rights Reserved.

Machine Learning and Data Mining in Pattern Recognition

Third International Conference, MLDM 2003, Leipzig, Germany, July 5-7, 2003, Proceedings

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