Advances in Data Mining and Modeling: Hong Kong 27 - 28 June 2002

by Ching, Wai-Ki; Ng, Michael Kwok-Po

• ISBN13: 9789812383549
• ISBN10: 9812383549
• Format: Hardcover
• Copyright: 2003-04-01
• Publisher: World Scientific Pub Co Inc

Summary

Data mining and data modeling are hot topics and are under fast development. Because of their wide applications and rich research contents, many practitioners and academics are attracted to work in these areas. With a view to promoting communication and collaboration among the practitioners and researchers in Hong Kong, a workshop on data mining and modeling was held in June 2002. Prof Ngaiming Mok, Director of the Institute of Mathematical Research, The University of Hong Kong, and Prof Tze Leung Lai (Stanford University), C V Starr Professor of the University of Hong Kong, initiated the workshop.This book contains selected papers presented at the workshop. The papers fall into two main categories: data mining and data modeling. Data mining papers deal with pattern discovery, clustering algorithms, classification and practical applications in the stock market. Data modeling papers treat neural network models, time series models, statistical models and practical applications.

Table of Contents

Preface	p. vii
Author Index	p. xiii
Data Mining
Algorithms for Mining Frequent Sequences	p. 1
High Dimensional Feature Selection for Discriminant Microarray Data Analysis	p. 15
Clustering and Cluster Validation in Data Mining	p. 25
Cluster Analysis Using Unidimensional Scaling	p. 40
Automatic Stock Trend Prediction by Real Time News	p. 48
From Associated Implication Networks to Intermarket Analysis	p. 60
Automating Technical Analysis	p. 85
Data Modeling
A Divide-and-Conquer Fast Implementation of Radial Basis Function Networks with Application to Time Series Forecasting	p. 97
Learning Sunspot Series Dynamics by Recurrent Neural Networks	p. 107
Independent Component Analysis: The One-Bit-Matching Conjecture and a Simplified LPM-ICA Algorithm	p. 116
An Higher-Order Markov Chain Model for Prediction of Categorical Data Sequences	p. 129
An Application of the Mixture Autoregressive Model: A Case Study of Modelling Yearly Sunspot Data	p. 142
Bond Risk and Return in the SSE	p. 152
Mining Loyal Customers: A Practical Use of the Repeat Buying Theory	p. 167
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