1. Dept. of Computing Science, University of Aberdeen1 CS4031/CS5012 Data Mining and Visualization Yaji Sripada

2. Dept. of Computing Science, University of Aberdeen2 Time table Lectures –2 lectures 11:00 -12:00 Tuesdaysin Taylor A21 10:00 – 11:00 Wednesdays in Meston 311 Practicals –1 two hour practical on Mondays in Meston 311 (Room changed since the last lecture) 15:00-17:00

3. Dept. of Computing Science, University of Aberdeen3 Assessment Course is worth 15 credits Two components –25% continuous assessment –75% end of term exam Continuous assessment –Issued in Week 6/7 –Due on the Friday of Week 10/11

4. Dept. of Computing Science, University of Aberdeen4 Course Organization Lectures –Discuss topics including Data Mining –General Data –Time series –Spatial data Information Visualization (InfoVis) Case Studies Practicals –10 weeks Mostly using some existing software Developing your own software (PHP) –8 th week assessment

5. Dept. of Computing Science, University of Aberdeen5 Reading Mostly lecture notes and some research papers I will provide all the required reading material

6. Dept. of Computing Science, University of Aberdeen6 Introduction

7. Dept. of Computing Science, University of Aberdeen7 Overgrowth of Data Humans accumulate large volumes of data in many domains –Business Transactional data –Scientific Complete sequence data from Human Genome Project –of 3 billion DNA units –Engineering 100s of sensors on a gas turbine taking measurements every second –And many more?

8. Dept. of Computing Science, University of Aberdeen8 Information Hidden in Data Data are raw facts Humans routinely ‘dig’ useful abstractions from raw data –An example abstraction ‘mined’ from past exam results –No coursework submitted => will fail the exam as well For small data sets (a few hundred bytes) –Simple and manual data analysis OK (Even preferred!!!) –Statistics For large data sets (a few Gigabytes or more) –Manual analysis is impossible –Computer Assistance needed

9. Dept. of Computing Science, University of Aberdeen9 Two views of computer assistance Data Mining View –Machines can automatically (or semi- automatically) extract meaningful and useful information from heaps of raw data Information Visualization (InfoVis) View –Humans themselves can make sense of data if data are presented visually We learn both these views in this course

10. Dept. of Computing Science, University of Aberdeen10 Data Mining Process of automatically (or semi- automatically) discovering useful, novel and meaningful patterns from substantial quantities of data. Tasks –Classification –Clustering –Association Rule Mining

11. Dept. of Computing Science, University of Aberdeen11 Typical Applications Customer Relationship Management (CRM) Linking gene variations among individuals to common illnesses (e.g. Cancer) Identifying abnormal conditions in an operational gas turbine More ?

12. Dept. of Computing Science, University of Aberdeen12 Information Visualization Process of representing data in such a way (usually involves visual presentations) that enable users to gain useful insights into the data Focus is on designing a data representation scheme that makes in underlying ‘information’ visible to the user For rendering the representation scheme –Computer graphics technology is exploited Good InfoVis techniques are based on –Good understanding of the information structures underlying the data –Good understanding of the human perception and cognition –Good graphics

13. Dept. of Computing Science, University of Aberdeen13 Typical Applications Newsmap Touchgraph ManyEyes CountryScape

14. Dept. of Computing Science, University of Aberdeen14 SVG Scalable Vector Graphics –An XML-based Web Language to textually specify vector graphics –E.g. SVG specification of a circle W3C Recommendation Browser support for SVG content –Firefox provides built in support –IE needs an Adobe Plug-in SVG content can be created –Using text editors (static) –Programmatically (dynamic)

15. Dept. of Computing Science, University of Aberdeen15 SVG in an HTML page Three methods Using the tag Using the tag – Using the tag –

16. Dept. of Computing Science, University of Aberdeen16 Learning SVG In this course focus is on designing effective visualizations –We assume knowledge of SVG for rendering the visualizations Fundamentals of SVG covered in lectures Some practicals involve SVG creation –No practicals exclusively for learning SVG

17. Dept. of Computing Science, University of Aberdeen17 Lectures Data Exploratory Data Analysis (EDA) Classification – I Classification – II Clustering – I Clustering – II InfoVis – I InfoVis – II InfoVis – III Association rule mining Time Series – I Time Series – II Time Series – III Sequence Mining Spatial Data GIS Spatial Data Mining Issues with Data mining and InfoVis Users Detailed Course Plan Practicals Exploratory Data Analysis (EDA) Classification Clustering HCE Tree Maps Association Rule Mining Assignment Time Searcher Time Series Representations GIS Exploring spatio-temporal Data

18. Dept. of Computing Science, University of Aberdeen18 Summary All modern organizations –possess large volumes of data and –Users want to understand these data You learn technologies to –Extract and/Or present information from large data sets Analytical methods Visualization methods