Knowledge Discovery in Databases

by Piatetsky-Shapiro, Gregory; Frawley, William J.

• ISBN13: 9780262660709
• ISBN10: 0262660709
• Format: Paperback
• Copyright: 1991-12-30
• Publisher: Aaai Pr

Summary

Knowledge Discovery in Databases brings together current research on the exciting problem of discovering useful and interesting knowledge in databases. It spans many different approaches to discovery, including inductive learning, bayesian statistics, semantic query optimization, knowledge acquisition for expert systems, information theory, and fuzzy 1 sets. The rapid growth in the number and size of databases creates a need for tools and techniques for intelligent data understanding. Relationships and patterns in data may enable a manufacturer to discover the cause of a persistent disk failure or the reason for consumer complaints. But today's databases hide their secrets beneath a cover of overwhelming detail. The task of uncovering these secrets is called "discovery in databases." This loosely defined subfield of machine learning is concerned with discovery from large amounts of possible uncertain data. Its techniques range from statistics to the use of domain knowledge to control search. Following an overview of knowledge discovery in databases, thirty technical chapters are grouped in seven parts which cover discovery of quantitative laws, discovery of qualitative laws, using knowledge in discovery, data summarization, domain?specific discovery methods, integrated and multi-paradigm systems, and methodology and application issues. An important thread running through the collection is reliance on domain knowledge, starting with general methods and progressing to specialized methods where domain knowledge is built in. Gregory Piatetski-Shapiro is Senior Member of Technical Staff and Principal Investigator of the Knowledge Discovery Project at GTE Laboratories. William Frawley is Principal Member of Technical Staff at GTE and Principal Investigator of the Learning in Expert Domains Project.

Table of Contents

Preface	p. vii
Foreword	p. ix
Knowledge Discovery in Databases: An Overview	p. 1
Discovery of Quantitative Laws
Interactive Mining of Regularities in Databases	p. 31
Discovering Functional Relationships from Observational Data	p. 55
Minimal-Length Encoding and Inductive Inference	p. 71
On Evaluation of Domain-Independent Scientific Function-Finding Systems	p. 93
Discovery of Qualitative Laws
A Statistical Technique for Extracting Classificatory Knowledge from Databases	p. 107
Information Discovery through Hierarchical Maximum Entropy Discretization and Synthesis	p. 125
Learning Useful Rules from Inconclusive Data	p. 141
Rule Induction Using Information Theory	p. 159
Incremental Discovery of Rules and Structure by Hierarchical and Parallel Clustering	p. 177
The Discovery, Analysis and Representation of Data Dependencies in Databases	p. 195
Using Knowledge in Discovery
Attribute-Oriented Induction in Relational Databases	p. 213
Discovery, Analysis, and Presentation of Strong Rules	p. 229
Integration of Heuristic and Bayesian Approaches in a Pattern-Classification System	p. 249
Using Functions to Encode Domain and Contextual Knowledge in Statistical Induction	p. 261
Integrated Learning in a Real Domain	p. 277
Induction of Decision Trees from Complex Structured Data	p. 289
Data Summarization
Summary Data Estimation Using Decision Trees	p. 309
A Support System for Interpreting Statistical Data	p. 325
On Linguistic Summaries of Data	p. 347
Domain-Specific Discovery Methods
Extracting Reaction Information from Chemical Databases	p. 367
Automated Knowledge Generation From a CAD Database	p. 383
Justification-Based Refinement of Expert Knowledge	p. 397
Rule Discovery for Query Optimization	p. 411
Integrated and Multiparadigm Systems
Unsupervised Discovery in an Operational Control Setting	p. 431
Mining for Knowledge in Databases: Goals and General Description of the INLEN System	p. 449
Methodology and Application Issues
Automating the Discovery of Causal Relationships in a Medical Records Database: The POSCH AI Project	p. 465
Discovery of Medical Diagnostic Information: An Overview of Methods and Results	p. 477
The Trade-Off between Knowledge and Data in Knowledge Acquisition	p. 491
Knowledge Discovery as a Threat to Database Security	p. 507
Index	p. 517
Table of Contents provided by Publisher. All Rights Reserved.