Discovery Science 5th International Conference, DS 2002, Lubeck, Germany, November 24-26, 2002, Proceedings /

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Lange, Steffen (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Satoh, Ken (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Smith, Carl H. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2002.
Έκδοση:1st ed. 2002.
Σειρά:Lecture Notes in Computer Science, 2534
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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-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.