Discovery science : 5th international conference, DS 2002, Lübeck, Germany, November 24-26, 2002 : proceedings
Gorde:
| Erakunde egilea: | |
|---|---|
| Beste egile batzuk: | , , |
| Formatua: | Livre numérique |
| Hizkuntza: | Anglais |
| Argitaratua: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Saila: | Lecture notes in computer science
2534 |
| Gaiak: | |
| Sarrera elektronikoa: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Oharra: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Discovery Science, Texte imprimé, 9783540001881 • Discovery Science, Texte imprimé, 9783662175415 |
Aurkibidea:
- 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
- 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-SweetnessRelationships 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.