Cover image for Advances in data mining and modeling : Hong Kong 27 - 28 June 2002
Title:
Advances in data mining and modeling : Hong Kong 27 - 28 June 2002
Publication Information:
Singapore : World Scientific Publishing, 2003
ISBN:
9789812383549
General Note:
"A two-day workshop on data mining and modelling was held on 27-28 June 2002. This book contains selected papers presented in the workshop."

Available:*

Library
Item Barcode
Call Number
Material Type
Item Category 1
Status
Searching...
30000004303404 QA76.9.D343 A38 2003 Open Access Book Book
Searching...

On Order

Summary

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

Ben Kao and Ming-Hua ZhangJu-Fu Feng and Jiang-Xin Shi and Qing-Yun ShiJoshua Zhe-Xue Huang and Hong-Qiang Rong and Jessica Ting and Yun-Ming Ye and Qi-Ming HuangPui-Lam Leung and Chi-Yin Li and Kin-Nam LauGabriel Pui-Cheong Fung and Jeffrey Xu Yu and Wai LamPhil Chi-Wang Tse and Ji-Ming LiuPhilip Leung-Ho Yu and Kin Lam and Sze-Hong NgRong-Bo Huang and Yiu-Ming Cheung and Lap-Tak LawLeong-Kwan LiZhi-Yong Liu and Kai-Chun Chiu and Lei XuWai-Ki Ching and Eric Siu-Leung Fung and Michael Kwok-Po NgKevin Kin-Foon Wong and Chun-Shan WongLong-Zhen FanHing-Po Lo and Xiao-Ling Lu and Zoe Sau-Chun Ng
Prefacep. vii
Author Indexp. xiii
Data Mining
Algorithms for Mining Frequent Sequencesp. 1
High Dimensional Feature Selection for Discriminant Microarray Data Analysisp. 15
Clustering and Cluster Validation in Data Miningp. 25
Cluster Analysis Using Unidimensional Scalingp. 40
Automatic Stock Trend Prediction by Real Time Newsp. 48
From Associated Implication Networks to Intermarket Analysisp. 60
Automating Technical Analysisp. 85
Data Modeling
A Divide-and-Conquer Fast Implementation of Radial Basis Function Networks with Application to Time Series Forecastingp. 97
Learning Sunspot Series Dynamics by Recurrent Neural Networksp. 107
Independent Component Analysis: The One-Bit-Matching Conjecture and a Simplified LPM-ICA Algorithmp. 116
An Higher-Order Markov Chain Model for Prediction of Categorical Data Sequencesp. 129
An Application of the Mixture Autoregressive Model: A Case Study of Modelling Yearly Sunspot Datap. 142
Bond Risk and Return in the SSEp. 152
Mining Loyal Customers: A Practical Use of the Repeat Buying Theoryp. 167