Machine learning and data mining in pattern recognition : third international conference, MLDM 2003, Leipzig, Germany, July 5 7, 2003 : proceedings
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 t...
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| Schriftenreihe: | Lecture notes in computer science. Lecture notes in artificial intelligence
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| Edition sous un autre format: | • Machine learning and data mining in pattern recognition, third international conference, MLDM 2003, Leipzig, Germany, July 5-7, 2003, proceedings, Petra Perner, Azriel Rosenfeld (eds.), Berlin, Springer, 2003, 1 vol. (XII-440 p.), Lecture notes in computer science, 3-540-40504-6 • Machine Learning and Data Mining in Pattern Recognition, Texte imprimé, 9783662198377 |
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| 100 | 1 | |a Perner, Petra, |d 1958- | |
| 245 | 1 | 0 | |a Machine learning and data mining in pattern recognition : |b third international conference, MLDM 2003, Leipzig, Germany, July 5 7, 2003 : proceedings |c [edited by] Petra Perner, Azriel Rosenfeld. |
| 260 | |a Berlin [etc.] : |b Springer. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Lecture notes in computer science. Lecture notes in artificial intelligence |v 2734 |x 1611-3349 |x 2945-9141 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 0 | |a 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. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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. | ||
| 650 | |a Informatique | ||
| 650 | |a Apprentissage automatique | ||
| 650 | |a Intelligence artificielle | ||
| 650 | |a Traitement d'images | ||
| 650 | |a Exploration de données | ||
| 650 | |a Logique symbolique et mathématique | ||
| 650 | |a Perception des structures | ||
| 650 | |a Informatique documentaire | ||
| 650 | |a Actes de congrès | ||
| 700 | 1 | |a Rosenfeld, Azriel, |d 1931-2004. |4 pbd | |
| 711 | 2 | |a MLDM 2003 |n (3rd |c :Leipzig, Germany). |4 aut | |
| 776 | 0 | |0 074428101 |t Machine learning and data mining in pattern recognition |o third international conference, MLDM 2003, Leipzig, Germany, July 5-7, 2003 |o proceedings |f Petra Perner, Azriel Rosenfeld (eds.) |c Berlin |n Springer |d 2003 |p 1 vol. (XII-440 p.) |s Lecture notes in computer science |z 3-540-40504-6 | |
| 776 | 0 | |t Machine Learning and Data Mining in Pattern Recognition |b Texte imprimé |z 9783662198377 | |
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