Progress in Discovery Science

This volume contains the research reports of the Discovery Science pro ject in Japan (No. 10143106),in which more than 60 scientists participated. It was a three-year pro ject sponsored by Grant-in-Aid for Scienti?c Research on Priority Areas from the Ministry of Education,Culture,Sports,Science,and Technology (MEXT) of Japan. This pro ject mainly aimed to (1) develop new methods for knowledge discovery,(2) install network environments for knowledge discovery, and (3) establish Discovery Science as a new area of study in Computer Science / Arti?cial Intelligence. In order to attain these aims we set up ?ve groups for studying the following research areas: (A) Logic for/of Knowledge Discovery (B) Knowledge Discovery by Inference/Reasoning (C) Knowledge Discovery Based on Computational Learning Theory (D) Knowledge Discovery in Huge Databases and Data Mining (E) Knowledge Discovery in Network Environments These research areas and related topics can be regarded as a preliminary d- inition of Discovery Science by enumeration. Thus Discovery Science ranges over philosophy,logic,reasoning,computational learning,and system developments. In addition to these ?ve research groups we organized a steering group for planning,adjustment,and evaluation of the project. The steering group,chaired by the principal investigator of the project,consists of leaders of the ?ve research groups and their subgroups as well as advisors from outside of the pro ject. We invited three scientists to consider Discovery Science and the ?ve above m- tioned research areas from viewpoints of knowledge science,natural language processing,and image processi ng,respectively.

Includes supplementary material: sn.pub/extras

Inhalt
Searching for Mutual Exclusion Algorithms Using BDDs.- Reducing Search Space in Solving Higher-Order Equations.- The Structure of Scientific Discovery: From a Philosophical Point of View.- Ideal Concepts, Intuitions, and Mathematical Knowledge Acquisitions in Husserl and Hilbert.- Theory of Judgments and Derivations.- Efficient Data Mining from Large Text Databases.- A Computational Model for Children's Language Acquisition Using Inductive Logic Programming.- Some Criterions for Selecting the Best Data Abstractions.- Discovery of Chances Underlying Real Data.- Towards the Integration of Inductive and Nonmonotonic Logic Programming.- EM Learning for Symbolic-Statistical Models in Statistical Abduction.- Refutable/Inductive Learning from Neighbor Examples and Its Application to Decision Trees over Patterns.- Constructing a Critical Casebase to Represent a Lattice-Based Relation.- On Dimension Reduction Mappings for Approximate Retrieval of Multi-dimensional Data.- Rule Discovery from fMRI Brain Images by Logical Regression Analysis.- A Theory of Hypothesis Finding in Clausal Logic.- Efficient Data Mining by Active Learning.- Data Compression Method Combining Properties of PPM and CTW.- Discovery of Definition Patterns by Compressing Dictionary Sentences.- On-Line Algorithm to Predict Nearly as Well as the Best Pruning of a Decision Tree.- Finding Best Patterns Practically.- Classification of Object Sequences Using Syntactical Structure.- Top-Down Decision Tree Boosting and Its Applications.- Extraction of Primitive Motion and Discovery of Association Rules from Human Motion Data.- Algorithmic Aspects of Boosting.- Automatic Detection of Geomagnetic Jerks by Applying a Statistical Time Series Model to Geomagnetic Monthly Means.- Application of Multivariate MaxwellianMixture Model to Plasma Velocity Distribution.- Inductive Thermodynamics from Time Series Data Analysis.- Mining of Topographic Feature from Heterogeneous Imagery and Its Application to Lunar Craters.- Application of Neural Network Technique to Combustion Spray Dynamics Analysis.- Computational Analysis of Plasma Waves and Particles in the Auroral Region Observed by Scientific Satellite.- A Flexible Modeling of Global Plasma Profile Deduced from Wave Data.- Extraction of Signal from High Dimensional Time Series: Analysis of Ocean Bottom Seismograph Data.- Foundations of Designing Computational Knowledge Discovery Processes.- Computing Optimal Hypotheses Efficiently for Boosting.- Discovering Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables.- Finding of Signal and Image by Integer-Type Haar Lifting Wavelet Transform.- In Pursuit of Interesting Patterns with Undirected Discovery of Exception Rules.- Mining from Literary Texts: Pattern Discovery and Similarity Computation.- Second Difference Method Reinforced by Grouping: A New Tool for Assistance in Assignment of ComplexMolecular Spectra.- Discovery of Positive and Negative Knowledge in Medical Databases Using Rough Sets.- Toward the Discovery of First Principle Based Scientific Law Equations.- A Machine Learning Algorithm for Analyzing String Patterns Helps to Discover Simple and Interpretable Business Rules from Purchase History.- Constructing Inductive Applications by Meta-Learning with Method Repositories.- Knowledge Discovery from Semistructured Texts.- Packet Analysis in Congested Networks.- Visualization and Analysis of Web Graphs.- Knowledge Discovery in Auto-tuning Parallel Numerical Library.- Extended Association Algorithm Based on ROC Analysis for Visual Information Navigator.- WWW Visualization Tools for Discovering Interesting Web Pages.- Scalable and Comprehensible Visualization for Discovery of Knowledge from the Internet.- Meme Media for Re-editing and Redistributing Intellectual Assets and Their Application to Interactive Virtual Information Materialization.