## Discovery Science: Second International Conference, DS'99, Tokyo, Japan, December 6-8, 1999 ProceedingsSetsuo Arikawa, Koichi Furukawa This volume contains the papers presented at the Second International Conf- ence on Discovery Science (DS'99), held in Tokyo, Japan, December 6-8, 1999. The conference was colocated with the Tenth International Conference on Al- rithmic Learning Theory (ALT'99). This conference was organized as part of the activities of the Discovery S- ence Project sponsored by Grant-in-Aid for Scienti c Research on Priority Area fromthe MinistryofEducation, Science, SportsandCulture (MESSC)ofJapan. This is a three-year project starting from 1998 that aims to (1) develop new methods for knowledge discovery, (2) install network environments for kno- edge discovery, and (3) establish Discovery Science as a new area of computer science. The aim of this conference is to provide an open forum for intensive disc- sions and interchange of new information among researchers working in the new area of Discovery Science. Topics of interest within the scope of this conference include, but are not limited to, the following areas: Logic for/of knowledge discovery, knowledge d- coverybyinferences, knowledgediscoverybylearningalgorithms, knowledged- coverybyheuristicsearch, scienti cdiscovery, knowledgediscoveryindatabases, data mining, knowledge discovery in network environments, inductive logic p- gramming, abductive reasoning, machine learning, constructive programming as discovery, intelligentnetworkagents, knowledgediscoveryfromunstructuredand multimedia data, statistical methods for knowledge discovery, data and kno- edge visualization, knowledge discovery and human interaction, and human f- tors in knowledge discovery. The DS'99 program committee selected 26 papers and 25 posters/demos from 74 submissions. Papers were selected according to their relevance to the conference, accuracy, signi cance, originality, and presentation quality. |

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### Contents

Principles for a New a Science | 1 |

Expressive Probability Models in Science | 13 |

Weighted Majority Decision among Several Region Rules for Scientific Discovery | 17 |

Classification by Aggregating Emerging Patterns | 30 |

An Appropriate Abstraction for an AttributeOriented Induction | 43 |

Collaborative Hypthesis Testing Processes by Interactive Production Systems | 56 |

Computer Aided Discovery of Users Hidden Interest for Query Restructuring | 68 |

Iterative Naive Bayes | 80 |

A Defintion of Discovery in Terms of Generalized Descriptional Complexity | 316 |

Feature Selection Using Consistency Measure | 319 |

A Model of Childrens Vocabulary Acquisition Using Inductive Logic Programming | 321 |

Automatic Acquisition of Image Processing Procedures from Sample Sets fo Classified Images Based on Requirement of Misclassification Rate | 323 |

Thermodynamics from Time Series Data Analysis | 326 |

Developing a Knowledge Network of URLs | 328 |

Derivation of the Topology Structure from Massive Graph Data | 330 |

Mining Association Algorithm Based on ROC Convex Hull Method in Bibliographic Navigation System | 333 |

Schema Design for Causal Law Mining from Incomplete Database | 92 |

Design and Evaluation of an Environment to Automate the Construction of Inductive Applications | 103 |

System for Assisting in Discovery | 115 |

Discovering Poetic Allusion in Anthologies of Classical Japanese Poems | 128 |

Characteristic Sets of Strings Common to SemiStructured Documents | 139 |

Approximation of Optimal TwoDimensional Association Rules for Categorical Attributes Using Semidefinite Programming | 148 |

Data Mining of Generalized Association Rules Using a Method of PartialMatch Retrieval | 160 |

Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms | 172 |

Scheduled Discovery of Exception Rules | 184 |

Learning in Constraint Databases | 196 |

Discover Risky Active Faults by Indexing an Earthquake Sequence | 208 |

Machine Discovery Based on the Cooccurence of References in a Search Engine | 220 |

Smoothness Prior Approach to Explore the Mean Structure in Large Time Series Data | 230 |

Automatic Detection of Geomagnetic Sudden Commencement Using Lifting Wavelet Filters | 242 |

A Noise Resistant Model Inference System | 252 |

A Graphical Method for Parameter Learning of SymbolicStatistical Models | 264 |

Parallel Execution for Speeding Up Inductive Logic Programming Systems | 277 |

Discovery of a Set Nominally Conditioned Polynomials | 287 |

A Dimension Reduction Mapping for a Approximate Retrieval of MultiDimensional Data | 299 |

Normal Form Transformation for Object Recognition Based on Support Vector Machines | 306 |

Regularization of Linear Regression Models in Various Metric Spaces | 335 |

ArgumentBased Agent Systems | 338 |

GraphBased Induction for General Graph Structured Data | 340 |

Rules Extraction by Constructive Learning of Neural Networks and HiddenUnit Clustering | 343 |

Weighted Majority Decision among Region Rules for a Categorical Dataset | 345 |

Rule Discovery Technique Using GP with Crossover to Maintain Variety | 347 |

From Visualization to Interactive Animation of Database Records | 349 |

Extraction of Primitive Motion for Human Motion Recognition | 351 |

Finding Meaningful Regions Containing Given Keywords from Large Text Collections | 353 |

Mining Adaptation Rules from Cases in CBR Systems | 355 |

An Automatic Acquisition of Acoustical Units for Speech Recognition Based on Hidden Markov Network | 357 |

Knowledge Discovery from Health Data Using Weighted Aggregation Classifiers | 359 |

Search for New Methods for Assignment of Complex Molecular Spectra | 362 |

Automatic Discovery of Definition Patterns Based on the MDL Principle | 364 |

Detection of the Structure of Particle Velocity Distribution by Finite Mixture Distribution Model | 366 |

Mutagenes Discovery Using PC GUHA Software System | 369 |

Discovering the Primary Factors of Cancer from Health and Living Habit Questionnaires | 371 |

373 | |

### Other editions - View all

Discovery Science: Second International Conference, DS'99, Tokyo, Japan ... Setsuo Arikawa,Koichi Furukawa No preview available - 2014 |

Discovery Science: Second International Conference, DS'99, Tokyo, Japan ... Setsuo Arikawa,Koichi Furukawa No preview available - 1999 |

### Common terms and phrases

abstraction accuracy algorithm applied Arikawa Artificial Intelligence association rules AVL tree Bayesian Bayesian networks Berlin Heidelberg 1999 CAEP CAMLET characteristic set classifier clusters components Computer consider constraints constructed data mining database dataset decision tree defined denote discovered distribution domain earthquakes efficient EM algorithm evaluation experiments faults function Furukawa Eds given graph H-Map hierarchy hypothesis images Inductive Logic Programming input instances Iterative Jaccard coefficient Japan keywords Knowledge Discovery LNAI Logic Programming Machine Learning method metric space naive Bayes naive Bayes classifier negative examples node Nrmis obtained optimal paper parameters partial-match pattern prediction problem Proc proposed Ptest ratio region rules relation rule pairs sample Science search query selected sequence space specific Springer-Verlag Berlin Heidelberg strategy string structure suffix tree Table target threshold tuples URLs user interest user’s variables vector viewscopes wavelet filters