文档介绍：Overview
Introduction
Data warehouse & OLAP technology
Data processing
DM primitives, languages & system architectures
Concept description: characterization & comparison
Mining association rules in large databases
Classification and prediction
Cluster analysis
plex types of data
Applications and trends
Contents
教学方式与考核方式
教学方式
本课程以课堂教学为主,以电子教案的内容为主线
课外阅读指定的参考文献并利用网上资源,加深对教学内容的理解。
轮流进行报告,每人一次。
考核方式及要求
撰写课程论文一篇
课程论文的内容包括数据仓库与数据挖掘综述,或者对某一方面的分析、独立的见解或实际应用。
课程论文的格式按照正式发表学术论文的要求,篇幅一般可大于正式发表的论文。
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教材与参考书
Jiawei Han, Micheline Kambr,《DATA MINING CONCEPTS AND TECHNIQUES》(影印版),高等教育出版社
康晓东等《基于数据仓库的数据挖掘技术》,***出版社,
邵峰晶等,《数据挖掘-原理与算法》,中国水利水电出版社,
林杰斌等,《数据挖掘与OLAP理论与实务》,清华大学出版社,
C. Seidman:《SQL SERVER 2000数据挖掘技术指南》,***出版社,
因特网上有关参考资料和文献
学术刊物上有关论文
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Han Jiawei
Professor, Department puter Science Univ. of Illinois at Urbana-Champaign Rm 2132, Siebel Center puter Science 201 N. Goodwin Avenue Urbana, IL 61801, USA . (1985), Computer Science, Univ. Wisconsin-Madison
Data Mining and Database Systems
Data Mining Research Group Database and Information Systems Research Laboratory (UIUC Academic Calendar) Fax: (217) 265-6494
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韩家炜
韩家炜:早年就读于郑州大学,在美国威斯康辛大学获得硕士和博士学位。毕业后,曾在美国西北大学任教,1988年起在加拿大西蒙弗雷泽大学任教。
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Contents
Contents Foreword Preface Chapter 1 Introduction What Motivated Data Mining? Why is it important? So, What is Data Mining? Data Mining-On What Kind of Data? Relational Databases Data Warehouses Transactional Databases Advanced Database Systems and Advanced Database Applications Data Mining Functionalities—What Kinds of Patterns Can Be Mined? Concept/Class Description: Characterization and Discrimination Association analysis Classification and Prediction Cluster Analysis Outlier Analysis Evolution analysis Are All of the Patterns Interesting? classification of Data Mining systems major lssues in data Mining summary Ex