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Record Nr. |
UNINA9910208852403321 |
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Titolo |
Discovery Science : 5th International Conference, DS 2002, Lubeck, Germany, November 24-26, 2002, Proceedings / / edited by Steffen Lange, Ken Satoh, Carl H. Smith |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2002 |
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ISBN |
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Edizione |
[1st ed. 2002.] |
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Descrizione fisica |
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1 online resource (XIV, 470 p.) |
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Collana |
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Lecture Notes in Computer Science, , 0302-9743 ; ; 2534 |
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Disciplina |
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Soggetti |
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Database management |
Philosophy and science |
Computer science |
Information storage and retrieval |
Artificial intelligence |
Information technology |
Business—Data processing |
Database Management |
Philosophy of Science |
Computer Science, general |
Information Storage and Retrieval |
Artificial Intelligence |
IT in Business |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Invited Talks -- Mathematics Based on Learning -- Data Mining with Graphical Models -- On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum -- In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project -- Learning Structure from Sequences, with Applications in a Digital Library -- Regular Papers -- Discovering Frequent Structured Patterns from String Databases: An Application to Biological Sequences -- Discovery in Hydrating Plaster Using Machine Learning Methods -- |
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Revising Qualitative Models of Gene Regulation -- SEuS: Structure Extraction Using Summaries -- Discovering Best Variable-Length-Don’t-Care Patterns -- A Study on the Effiect of Class Distribution Using Cost-Sensitive Learning -- Model Complexity and Algorithm Selection in Classification -- Experiments with Projection Learning -- Improved Dataset Characterisation for Meta-learning -- Racing Committees for Large Datasets -- From Ensemble Methods to Comprehensible Models -- Learning the Causal Structure of Overlapping Variable Sets -- Extraction of Logical Rules from Data by Means of Piecewise-Linear Neural Networks -- Structuring Neural Networks through Bidirectional Clustering of Weights -- Toward Drawing an Atlas of Hypothesis Classes: Approximating a Hypothesis via Another Hypothesis Model -- Datascape Survey Using the Cascade Model -- Learning Hierarchical Skills from Observation -- Poster Papers -- Image Analysis for Detecting Faulty Spots from Microarray Images -- Inferring Gene Regulatory Networks from Time-Ordered Gene Expression Data Using Differential Equations -- DNA-Tract Curvature Profile Reconstruction: A Fragment Flipping Algorithm -- Evolution Map: Modeling State Transition of Typhoon Image Sequences by Spatio-Temporal Clustering -- Structure-Sweetness Relationships of Aspartame Derivatives by GUHA -- A Hybrid Approach for Chinese Named Entity Recognition -- Extraction of Word Senses from Human Factors in Knowledge Discovery -- Event Pattern Discovery from the Stock Market Bulletin -- Email Categorization Using Fast Machine Learning Algorithms -- Discovery of Maximal Analogies between Stories -- Automatic Wrapper Generation for Multilingual Web Resources -- Combining Multiple K-Nearest Neighbor Classifiers for Text Classification by Reducts -- ARISTA Causal Knowledge Discovery from Texts -- Knowledge Discovery as Applied to Music: Will Music Web Retrieval Revolutionize Musicology? -- Process Mining: Discovering Direct Successors in Process Logs -- The Emergence of Artificial Creole by the EM Algorithm -- Generalized Musical Pattern Discovery by Analogy from Local Viewpoints -- Using Genetic Algorithms-Based Approach for Better Decision Trees: A Computational Study -- Handling Feature Ambiguity in Knowledge Discovery from Time Series -- A Compositional Framework for Mining Longest Ranges -- Post-processing Operators for Browsing Large Sets of Association Rules -- Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction -- Feature Selection for Propositionalization -- Subspace Clustering Based on Compressibility -- The Extra-Theoretical Dimension of Discovery Extracting Knowledge by Abduction -- Discovery Process on the WWW: Analysis Based on a Theory of Scientific Discovery -- Invention vs. Discovery A Critical Discussion. |
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