Active mining : new directions of data mining / edited by Hiroshi Motoda.

Format:

Book

Contributor:

Motoda, Hiroshi.

Series:

Frontiers in artificial intelligence and applications ; v. 79.

Frontiers in artificial intelligence and applications. Knowledge-based intelligent engineering systems ; v. 3.

Frontiers in artificial intelligence and applications, 0922-6389 ; v. 79. Knowledge-based intelligent engineering systems ; v. 3

Language:

English

Subjects (All):

Data mining.

Physical Description:

x, 291 p. : ill.

Edition:

1st ed.

Place of Publication:

Amsterdam ; Washington, DC : IOS Press ; Tokyo : Ohmsha, c2002.

Language Note:

English

Summary:

Focusing on data mining, this work is a joint effort from researchers in Japan, and includes a report on the forefront of data collection, user-centred mining and user interaction/reaction. It offers an overview of modern solutions with real-world applications, sharing hard-learned experiences.

Contents:

Cover

Title page

Preface

Acknowledgments

Contents

I. Data Collection

Toward Active Mining from On-line Scientific Text Abstracts Using Pre-existing Sources

Data Mining on the WAVEs - Word-of-mouth-Assisting Virtual Environments

Immune Network-based Clustering for WWW Information Gathering/Visualization

Interactive Web Page Retrieval with Relational Learning-based Filtering Rules

Monitoring Partial Update of Web Pages by Interactive Relational Learning

Context-based Classification of Technical Terms Using Support Vector Machines

Intelligent Tickers: An Information Integration Scheme for Active Information Gathering

II. User Centered Mining

Discovery of Concept Relation Rules Using an Incomplete Key Concept Dictionary

Mining Frequent Substructures from Web

Towards the Discovery of Web Communities from Input Keywords to a Search Engine

Temporal Spatial Index Techniques for OLAP in Traffic Data Warehouse

Knowledge Discovery from Structured Data by Beam-wise Graph-Based Induction

PAGA Discovery: A Worst-Case Analysis of Rule Discovery for Active Mining

Evaluating the Automatic Composition of Inductive Applications Using StatLog Repository of Data Set

Fast Boosting Based on Iterative Data Squashing

Reducing Crossovers in Reconciliation Graphs Using the Coupling Cluster Exchange Method with a Genetic Algorithm

Outlier Detection using Cluster Discriminant Analysis

III. User Reaction and Interaction

Evidence-Based Medicine and Data Mining: Developing a Causal Model via Meta-Learning Methodology

KeyGraph for Classifying Web Communities

Case Generation Method for Constructing an RDR Knowledge Base

Acquiring Knowledge from Both Human Experts and Accumulated Data in an Unstable Environment.

Active Participation of Users with Visualizaiton Tools in the Knowledge Discovery Process

The Future Direction of Active Mining in the Business World

Topographical Expression of a Rule for Active Mining

The Effect of Spatial Representation of Information on Decision Making in Purchase

A Hybrid Approach of Multiscale Matching and Rough Clustering to Knowledge Discovery in Temporal Medical Databases

Meta Analysis for Data Mining

Author Index

A

B

C

F

H

I

K

M

N

O

S

T

U

W

Y.

Notes:

Bibliographic Level Mode of Issuance: Monograph

Includes bibliographical references and author index.

ISBN:

600-00-0325-0

9786610505555

1-60129-400-X

1-280-50555-9

OCLC:

53020578