INTRODUCTION TO DATA MINING (数据挖掘)

1) For undergraduate students in Computer Science major

2) South campus, GDUFS

3) Starting at September 2016; March 2017; September 2017; March 2018

4) 48 study scores in total

5) Scheduled as 16 weeks in total (16*3, 1~2 weeks for each chapter)

Teaching Materials:

1) 《数据挖掘原理与实践》，蒋盛益等著，电子工业出版社，2011

2) 《商务数据挖掘与应用案例分析》，蒋盛益著，电子工业出版社，2014

3) Pang-Ning Tan, Michael Steinbach, Vipin Kumar. Introduction to Data Mining.

(美)谭,(美)斯坦巴赫 著,范明等译.数据挖掘导论, 图灵计算机科学丛书. 人民邮电出版社.2006

4) Jiawei Han, Micheline Kamber, Jian Pei. Data Mining: Concepts and Techniques
(加)韩家炜,堪博(Kam ber, M.)著,范明,孟小峰译.数据挖掘概念与技术(原书第2版). 机械工业出版社.2007

5) Ian H. Witten, Eibe Frank, Mark A. Hall. Data Mining Practical Machine Learning Tools and Techniques.Morgan Kaufmann Publishers
Ian H. Witten, Eibe Frank, Mark A. Hall 著, 李川等译. 数据挖掘-实用机器学习工具与技术. 机械工业出版社

6) 袁梅宇著. 数据挖掘与机器学习WEKA应用技术与实践. 清华大学出版社. 2014

7) Peter Harrington. Machine Learning in Action.
(美)Peter Harrington, 李锐等译. 机器学习实战.图灵计算机科学丛书. 人民邮电出版社. 2013

8) Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman. Mining of Massive Datasets (Second Edition)
(美)Jure Leskovec等著, 王斌译. 互联网大规模数据挖掘与分布式处理.图灵计算机科学丛书. 人民邮电出版社. 2015

Practice resource:

1) Weka 3: Data Mining Software in Java

2) Downloading and installing Weka

3) General Weka documentation (manual Weka 3.8.0)

4) Collections of Datasets

Related resources:

1) 《Introduction to Data Mining》 by Pang-Ning Tan, Michael Steinbach, Vipin Kumar, University of Minnesota, course resource

2) 《Introduction to Data Mining》 by Prof. Qiang Yang, 香港科技大学, course resource

3) 《Data Mining》 by Prof. Chris Clifton, Purdue University, course resource