08028nam 22008295 450 991076753610332120251116234343.03-540-45065-31-4175-6476-810.1007/3-540-45065-3(CKB)1000000000212085(DE-He213)978-3-540-45065-8(SSID)ssj0000195095(PQKBManifestationID)11182027(PQKBTitleCode)TC0000195095(PQKBWorkID)10241133(PQKB)10654899(MiAaPQ)EBC3073320(PPN)155166778(EXLCZ)99100000000021208520121227d2003 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierMachine Learning and Data Mining in Pattern Recognition Third International Conference, MLDM 2003, Leipzig, Germany, July 5-7, 2003, proceedings /edited by Petra Perner, Azriel Rosenfeld1st ed. 2003.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2003.1 online resource (XII, 444 p.) Lecture Notes in Artificial Intelligence ;2734Bibliographic Level Mode of Issuance: Monograph3-540-40504-6 Includes bibliographical references at the end of each chapters and index.Invited Talkes -- Introspective Learning to Build Case-Based Reasoning (CBR) Knowledge Containers -- Graph-Based Tools for Data Mining and Machine Learning -- Decision Trees -- Simplification Methods for Model Trees with Regression and Splitting Nodes -- Learning Multi-label Alternating Decision Trees from Texts and Data -- Khiops: A Discretization Method of Continuous Attributes with Guaranteed Resistance to Noise -- On the Size of a Classification Tree -- Clustering and Its Applications -- A Comparative Analysis of Clustering Algorithms Applied to Load Profiling -- Similarity-Based Clustering of Sequences Using Hidden Markov Models -- Support Vector Machines -- A Fast Parallel Optimization for Training Support Vector Machine -- A ROC-Based Reject Rule for Support Vector Machines -- Case-Based Reasoning -- Remembering Similitude Terms in CBR -- Authoring Cases from Free-Text Maintenance Data -- Classification, Retrieval, and Feature Learning -- Classification Boundary Approximation by Using Combination of Training Steps for Real-Time Image Segmentation -- Simple Mimetic Classifiers -- Novel Mixtures Based on the Dirichlet Distribution: Application to Data and Image Classification -- Estimating a Quality of Decision Function by Empirical Risk -- Efficient Locally Linear Embeddings of Imperfect Manifolds -- Dissimilarity Representation of Images for Relevance Feedback in Content-Based Image Retrieval -- A Rule-Based Scheme for Filtering Examples from Majority Class in an Imbalanced Training Set -- Coevolutionary Feature Learning for Object Recognition -- Discovery of Frequently or Sequential Patterns -- Generalization of Pattern-Growth Methods for Sequential Pattern Mining with Gap Constraints -- Discover Motifs in Multi-dimensional Time-Series Using the Principal Component Analysis and the MDL Principle -- Optimizing Financial Portfolios from the Perspective of Mining Temporal Structures of Stock Returns -- Visualizing Sequences of Texts Using Collocational Networks -- Complexity Analysis of Depth First and FP-Growth Implementations of APRIORI -- Bayesian Models and Methods -- GO-SPADE: Mining Sequential Patterns over Datasets with Consecutive Repetitions -- Using Test Plans for Bayesian Modeling -- Using Bayesian Networks to Analyze Medical Data -- A Belief Networks-Based Generative Model for Structured Documents. An Application to the XML Categorization -- Neural Self-Organization Using Graphs -- Association Rules Mining -- Integrating Fuzziness with OLAP Association Rules Mining -- Discovering Association Patterns Based on Mutual Information -- Applications -- Connectionist Probability Estimators in HMM Arabic Speech Recognition Using Fuzzy Logic -- Shape Recovery from an Unorganized Image Sequence -- A Learning Autonomous Driver System on the Basis of Image Classification and Evolutional Learning -- Detecting the Boundary Curve of Planar Random Point Set -- A Machine Learning Model for Information Retrieval with Structured Documents.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.Lecture Notes in Artificial Intelligence ;2734Artificial intelligenceLogic, Symbolic and mathematicalDatabase managementInformation storage and retrievalOptical data processingPattern perceptionArtificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Mathematical Logic and Formal Languageshttps://scigraph.springernature.com/ontologies/product-market-codes/I16048Database Managementhttps://scigraph.springernature.com/ontologies/product-market-codes/I18024Information Storage and Retrievalhttps://scigraph.springernature.com/ontologies/product-market-codes/I18032Image Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XArtificial intelligence.Logic, Symbolic and mathematical.Database management.Information storage and retrieval.Optical data processing.Pattern perception.Artificial Intelligence.Mathematical Logic and Formal Languages.Database Management.Information Storage and Retrieval.Image Processing and Computer Vision.Pattern Recognition.006.3/1Perner Petraedthttp://id.loc.gov/vocabulary/relators/edtRosenfeld Azrieledthttp://id.loc.gov/vocabulary/relators/edtInternational Workshop MLDM 2003MiAaPQMiAaPQMiAaPQBOOK9910767536103321Machine Learning and Data Mining in Pattern Recognition772451UNINA