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Discovery Science: Second International Conference, DS'99, Tokyo, Japan, December 6-8, 1999 Proceedings: Lecture Notes in Computer Science, cartea 1721

Editat de Setsuo Arikawa, Koichi Furukawa
en Limba Engleză Paperback – 18 noi 1999

Din seria Lecture Notes in Computer Science

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Specificații

ISBN-13: 9783540667131
ISBN-10: 354066713X
Pagini: 392
Ilustrații: XII, 380 p.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.55 kg
Ediția:1999
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Invited Papers.- The Melting Pot of Automated Discovery: Principles for a New Science.- Expressive Probability Models in Science.- Contributed Papers.- Weighted Majority Decision among Several Region Rules for Scientific Discovery.- CAEP: Classification by Aggregating Emerging Patterns.- An Appropriate Abstraction for an Attribute-Oriented Induction.- Collaborative Hypothesis Testing Processes by Interactive Production Systems.- Computer Aided Discovery of User’s Hidden Interest for Query Restructuring.- Iterative Naive Bayes.- Schema Design for Causal Law Mining from Incomplete Database.- Design and Evaluation of an Environment to Automate the Construction of Inductive Applications.- Designing Views in HypothesisCreator: System for Assisting in Discovery.- Discovering Poetic Allusion in Anthologies of Classical Japanese Poems.- Characteristic Sets of Strings Common to Semi-structured Documents.- Approximation of Optimal Two-Dimensional Association Rules for Categorical Attributes Using Semidefinite Programming.- Data Mining of Generalized Association Rules Using a Method of Partial-Match Retrieval.- Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms.- Scheduled Discovery of Exception Rules.- Learning in Constraint Databases.- Discover Risky Active Faults by Indexing an Earthquake Sequence.- Machine Discovery Based on the Co-occurrence of References in a Search Engine.- Smoothness Prior Approach to Explore the Mean Structure in Large Time Series Data.- Automatic Detection of Geomagnetic Sudden Commencement Using Lifting Wavelet Filters.- A Noise Resistant Model Inference System.- A Graphical Method for Parameter Learning of Symbolic-Statistical Models.- Parallel Execution for Speeding Up Inductive Logic Programming Systems.- Discovery of a Set ofNominally Conditioned Polynomials.- H-Map: A Dimension Reduction Mapping for Approximate Retrieval of Multi-dimensional Data.- Normal Form Transformation for Object Recognition Based on Support Vector Machines.- Posters.- A Definition of Discovery in Terms of Generalized Descriptional Complexity.- Feature Selection Using Consistency Measure.- A Model of Children’s Vocabulary Acquisition Using Inductive Logic Programming.- Automatic Acquisition of Image Processing Procedures from Sample Sets of Classified Images Based on Requirement of Misclassification Rate.- “Thermodynamics” from Time Series Data Analysis.- Developing a Knowledge Network of URLs.- Derivation of the Topology Structure from Massive Graph Data.- Mining Association Algorithm Based on ROC Convex Hull Method in Bibliographic Navigation System.- Regularization of Linear Regression Models in Various Metric Spaces.- Argument-Based Agent Systems.- Graph-Based Induction for General Graph Structured Data.- Rules Extraction by Constructive Learning of Neural Networks and Hidden-Unit Clustering.- Weighted Majority Decision among Region Rules for a Categorical Dataset.- Rule Discovery Technique Using GP with Crossover to Maintain Variety.- From Visualization to Interactive Animation of Database Records.- Extraction of Primitive Motion for Human Motion Recognition.- Finding Meaningful Regions Containing Given Keywords from Large Text Collections.- Mining Adaptation Rules from Cases in CBR Systems.- An Automatic Acquisition of Acoustical Units for Speech Recognition Based on Hidden Markov Network.- Knowledge Discovery from Health Data Using Weighted Aggregation Classifiers.- Search for New Methods for Assignment of Complex Molecular Spectra.- Automatic Discovery of Definition Patterns Based on the MDLPrinciple.- Detection of the Structure of Particle Velocity Distribution by Finite Mixture Distribution Model.- Mutagenes Discovery Using PC GUHA Software System.- Discovering the Primary Factors of Cancer from Health and Living Habit Questionnaires.

Caracteristici

Includes supplementary material: sn.pub/extras