美国克莱顿州立大学（Clayton State University ）计算机科学与信息技术系教授Junfeng Qu博士自7月2日到南开大学访问并开设Seminar，以下是Seminar的大纲，欢迎感兴趣的师生参加（面向信息资源管理系本科生，也欢迎感兴趣的同学和老师参加）！
时间：
7月2日周一，上午1-4节
7月3日周二，上午1-4节
7月4日周三，上午1-4节
7月5号周四，上午1-4节
地点：二主楼A104
Junfeng Qu教授的主要研究领域包括数据科学，知识工程与发现，软件工程，软件测试与质量保证，计算机游戏开发与设计，图像处理与计算机视觉。请有兴趣参加的师生提前注册，注册邮件请发送到李颖老师的邮箱（liying@nankai.edu.cn），邮件请注明姓名、年级、专业及研究方向。
Visual Analytics and Data Visualization Tools
Junfeng Qu, Ph.D.
Professor
Department of Computer Science and Information Technology
College of Information & Mathematical Sciences
Clayton State University, USA
Visual analytics has a wide spectrum of applications such as finance, business, medical, health care,insurance, money laundering, capital crimes, terrorism, security, internet security, and network analysisetc. People use visualization tools and techniques to synthesize information and derive insightfrom massive, dynamic, ambiguous, and often conflicting data. The overall goal is to detect theexpected and discover the unexpected. Data visualization and mining is a multidisciplinary field,we will focus on the following areas:
1. Data representations and transformations techniques that covers the datatransformation and conversion of data in ways that support visualization and analysis
2. Analytical reasoning techniques that enable users to obtain deep insights to support assessment, planning, and decision making
3. Visual reorientations and interaction techniques that take advantage of the human perception principles to allow users to see, explore, and understand large amounts of information
Schedule:
Lecture | Topic | Reading(GAV) |
1 | Introduction, information visualization | Chapter 1, 2 |
2 | Data collection, clean | Chapter 3 |
3 | Stats and Layout | Chapter 4 |
4 | Perception and Visual Attributes | Chapter 5 |
5 | Explore and Explain | Chapter 6 |
6 | Visualization tools | Chapter 7 |
7 | D3 Basic | Chapter 8 |
8 | Data Relationships | Chapter 9 |
9 | Hierarchies | Chapter 10 |
10 | Communities | Chapter 11 |
11 | Flows | Chapter 12 |
12 | Spatial Networks | Chapter 13 |
13 | Design | Chapter 16 |
14 | Big Data | Chapter 14 |
15 | Project presentation |
Prerequisites:
Basic programming concept, Computer Operating System knowledge and file operations
Course Materials & Readings:
Graph Analysis and Visualization (GAV), Richard Brath and David Jonker, Wiley 2015
ISBN: 978‐1‐118‐84584‐4
Illuminating the Path edited by J. Thomas and K. Cook, IEEE Press, 2006
http://vis.pnnl.gov/pdf/RD_Agenda_VisualAnalytics.pdf
Software tools:
Gephi: https://gephi.org/users/download/
Cytoscape: www.cytoscape.org
D3: https://github.com/d3/d3
NodeXL: http://nodexl.codeplex.com
Aperture JS: http://aperturejs.com/
yEd: https://www.yworks.com/products/yed/download
