Introduction to Information Visualization
|
|
|
- Patience Green
- 9 years ago
- Views:
Transcription
1 Universidade de Aveiro Departamento de Electrónica, Telecomunicações e Informática Introduction to Information Visualization Information Visualization Beatriz Sousa Santos, 2015/2016
2 What is Visualization? Is a method of Computing. It transforms the symbolic in the geometric, enabling researchers to observe simulations and computations providing scientific insight through visual methods (McCormick et al., 1987) Is concerned with exploring data and information graphically in such a way as to gain understanding and insight into the data (Brodlie et al., 1992) Means the study, development and use of graphics representation and supporting techniques that facilitate the visual communication of knowledge (Keller & Keller, 1993) A computationally intense visual thinking (Rhyne, 2002)
3 What is Information Visualization? The interdisciplinary study of the visual representation of large-scale collection of non-numerical information, such as files and lines of code in software systems, library and bibliographic databases, networks of relations on the internet, and so forth. (Friendly, 2008)
4 This course: InfoVis after an introduction to: Computer Graphics Data/Info Visualization Visual perception some materials in Moodle
5 Outline: Introduction to Data and Information Visualization Introduction to Computer graphics: - Geometric transformations (2D, 3D) and Visualization (2D, 3D) - Introduction to visibility, illumination, surface rendering and color models Visual Perception Information Visualization: - Main issues - Data and Design - Representation - Presentation - Interaction - Evaluation Beatriz Sousa Santos + Paulo Dias
6 Lab Classes SVG, Three.js Visualization tools (Google Charts, D3, )
7 Main Bibliography Spence, R., Information Visualization, Design for Interaction, 2nd ed., Prentice Hall, 2007 Munzner, T., Visualization Analysis and Design, A K Peters/CRC Press, 2014 Mazza, R., Introduction to Information Visualization, Springer, 2009 Ware, C., Information Visualization, Perception to Design, 3nd ed.,morgan Kaufmann, 2012 Hearn, D., Pauline Baker, Computer Graphics with OpenGL, 3rd ed., Prentice Hall, 2004
8 Other Bibliography Bederson, B., B. Shneiderman, The Craft of Information Visualization: Readings and Reflections, Morgan Kaufmann, 2003 Card, S., J. Mackinlay, and B. Shneiderman, Readings in Information Visualization: Using Vision to Think, Morgan Kaufmann, 1999 Tufte, E., The Visual Display of Quantitative Information, Graphics Press, 1983 Tufte, E., Envisioning Information, Graphics Press, 1990 Friendly, M., "Milestones in the history of thematic cartography, statistical graphics, and data visualization, 2008 Foley, J., A. van Dam, S. Feiner, J. Hughes, R. Phillips, Introduction to Computer Graphics, Addison Wesley, 1993 Few, S., Data Visualization for Human Perception. In: Soegaard, M. and Dam, R. (eds.). The Encyclopedia of Human-Computer Interaction, 2nd Ed. The Interaction Design Foundation InfoVis Wiki Papers and sites
9 Sessions: Thursday 11h-13h; Thursday 14h-16h (subject to minor adjustments) 1 (11/02/16) - Introduction to the course 2 (11/02/16) - Introduction to the lab classes; Google Charts 3 (18/02/16) - Introduction to DataVis and InfoVis 4 (18/02/16) Google Tool Charts 5 (25/02/16) Introduction to CG 6 (25/02/16) Introduction to Three.js 7 (03/03/16) - Introduction to CG (cont.) (paper presentation) 8 (03/03/16) Introduction to Three.js 9 (10/03/16) Visual Perception (paper presentation) 10 (10/03/16) Introduction to Three.js, 1rst assignment 11 (17/03/16) Main issues in InfoVis (paper presentation) 12 (17/03/16) - Introduction to Three.js, 1rst assignment 13 (31/03/16) Representation: coding of value (paper presentation) 14 (31/03/16) - 1rst assignment
10 15 (07/04/16) Representation: coding of value (cont) (paper presentation) 16 (07/04/16) Introduction to SVG 17 (14/04/16) Representation: coding of relation (paper presentation) 18 (14/04/16) - Introduction to SVG 19 (21/04/16) Presentation of the 1rst assignment 20 (21/04/16) Presentation of the 1rst assignment 21 (28/04/16) Evaluation in Visualization (paper presentation) 22 (28/04/16) Assignment on evaluation 23 (5/05/16) Introduction to D3, 2nd assignment 24 (5/05/16) Introduction to D3, 2nd assignment 25 (19/05/16) Presentation and Interaction (paper presentation) 26 (19/05/16) Introduction to D3, 2nd assignment 27 (26/05/16) Experiment on evaluation 28 (26/05/16) Experiment on evaluation 29 (2/06/16) - Presentation and Interaction (cont) (paper presentation) 30 (2/06/16) 2nd assignment
11 Assessment - paper analysis, presentation and discussion 10% - assignment on evaluation 10% - exam 30% - 1 rst programming assignment 20% - 2 nd programming assignment 30%
12 Paper presentation schedule Thursday 11h-13h (subject to minor adjustments) (25/02/16) (03/03/16) (10/03/16) (17/03/16) 2 papers (31/03/16) (07/04/16) (14/04/16) (28/04/16) (05/05/16) (19/05/16) 2 papers (02/06/16) 2 papers
13 Assignments 1 rst programming assignment WebGL, Three.js 2 nd programming assignment - D3, Assignment on evaluation
14 Analyzing and presenting an Info Vis paper Each student must: Select an InfoVis paper (>=10 pages) from: - Vis IEEE Computer Graphics and Applications - IEEE Transactions on Visualization and Computer Graphics Propose it until 26/2/2016 to [email protected] Indicating preferences concerning presentation date Read the presentation guidelines Make a 20 minute presentation and submit the slides Help: Laramee, R. S. (2011). How to Read a Visualization Research Paper: Extracting the Essentials. IEEE Computer Graphics and Applications, May/June,
15 Students who work must contact the lecturer during the two first weeks to establish evaluation details Students profile? Any doubts, questions?
16 Bibliography-papers Rhyne, T. M., "Does the Difference between Information and Scientific Visualization Really Matter?, IEEE Computer Graphics and Applications, May/June, 2003, pp. 6-8 Rhyne, T. M., Scientific Visualization in the Next Millennium, IEEE Computer Graphics and Applications, Jan./Feb., 2002, pp Hibbard, B., Top Ten, Visualization Problems, SIGGRAPH Computer Graphics Newsletter, VisFiles, May 1999, Vol. 33, N.2 Johnson, C., Top Scientific Visualization Research Problems, IEEE Computer Graphics and Applications: Visualization Viewpoints, July/August, 2004, pp Eick, S., "Information Visualization at 10," IEEE Computer Graphics and Applications, vol. 25, no. 1, Jan/Feb, 2005, pp Keefe, D., Integrating Visualization and Interaction Research to Improve Scientific Workflows, IEEE Computer Graphics and Applications, vol. 30, no. 2, Mar/April, 2010, pp. 8-13
17 Interesting links
18 Until February, 28: Select from the list the papers you prefer Think about the presentation dates you prefer Send to 21
19 Recent job advertisement by a Portuguese Company DATA VISUALIZATION SPECIALIST (M/F): Mission: -Build advanced data analysis and questioning existing assumptions and processes, improving opportunities to business and IT leaders in order to influence how an organization approaches a business challenge by uncovering new insights in data Responsibilities: - Provide analytical data consulting on models, best practices and approaches to improve opportunities to business areas; - Interpret IT analytical results providing conclusions and recommendations in order to find new ways to add value to business; - Work closely with other teams, analysing data to build methodology, implement analysis and technology in order to help identify viable solutions to business problems; - Implement standard and proprietary algorithms to handle and process data.
20 Job Requirements: - Higher education degree in IT or Math Area; - Knowledge in SQL Language, database architecture and data mining; - Communication skills; - Proactive and organized approach to solving problems; - Proficiency in English.
Universidade de Aveiro Departamento de Electrónica, Telecomunicações e Informática. Introduction to Information Visualization
Universidade de Aveiro Departamento de Electrónica, Telecomunicações e Informática Introduction to Information Visualization www.portugal-migration.info Information Visualization Beatriz Sousa Santos,
Universidade de Aveiro Departamento de Electrónica, Telecomunicações e Informática. Evaluation in Data and Information Visualization
Universidade de Aveiro Departamento de Electrónica, Telecomunicações e Informática Evaluation in Data and Information Visualization Beatriz Sousa Santos, 2011/2012 1 Definition Visualization is the process
Outline. Fundamentals. Rendering (of 3D data) Data mappings. Evaluation Interaction
Outline Fundamentals What is vis? Some history Design principles The visualization process Data sources and data structures Basic visual mapping approaches Rendering (of 3D data) Scalar fields (isosurfaces
An example. Visualization? An example. Scientific Visualization. This talk. Information Visualization & Visual Analytics. 30 items, 30 x 3 values
Information Visualization & Visual Analytics Jack van Wijk Technische Universiteit Eindhoven An example y 30 items, 30 x 3 values I-science for Astronomy, October 13-17, 2008 Lorentz center, Leiden x An
CSCD18: Computer Graphics
CSCD18: Computer Graphics Professor: Office: Office hours: Teaching Assistant: Office hours: Lectures: Tutorials: Website: Leonid Sigal [email protected] [email protected] Room SW626 Monday 12:00-1:00pm
DEGREE CURRICULUM COMPUTER GRAPHICS AND MULTIMEDIA Master's Degree in Informatics Enginneering
Academic year 2015- DEGREE CURRICULUM COMPUTER GRAPHICS AND MULTIMEDIA Master's Degree in Informatics Enginneering Teaching staff: Francesc Sebé Feixas Subject's general information Subject name Typology
Computer Graphics (600.357 / 600.457) Prof. Misha Kazhdan [email protected]
Computer Graphics (600.357 / 600.457) Prof. Misha Kazhdan [email protected] Outline Introduction Syllabus Coursework Miscellaneous Introduction: What is CG? 2D image processing 3D object representation
UNIVERSITY OF MACAU DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE SFTW 463 Data Visualization Syllabus 1 st Semester 2011/2012 Part A Course Outline
Elective required course in Computer Science UNIVERSITY OF MACAU DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE SFTW 463 Data Visualization Syllabus 1 st Semester 2011/2012 Part A Course Outline Catalog
Introduction to Computer Graphics
Introduction to Computer Graphics Torsten Möller TASC 8021 778-782-2215 [email protected] www.cs.sfu.ca/~torsten Today What is computer graphics? Contents of this course Syllabus Overview of course topics
COSC 6344 Visualization
COSC 64 Visualization University of Houston, Fall 2015 Instructor: Guoning Chen [email protected] Course Information Location: AH 2 Time: 10am~11:am Tu/Th Office Hours: 11:am~12:pm Tu /Th or by appointment
CSE452 Computer Graphics
CSE452 Computer Graphics Spring 2015 CSE452 Introduction Slide 1 Welcome to CSE452!! What is computer graphics? About the class CSE452 Introduction Slide 2 What is Computer Graphics? Modeling Rendering
The Visualization Pipeline
The Visualization Pipeline Conceptual perspective Implementation considerations Algorithms used in the visualization Structure of the visualization applications Contents The focus is on presenting the
City University of Hong Kong
City University of Hong Kong Information on a Course offered by School of Creative Media with effect from Semester A in 2012 / 2013 Part I Course Title: 3D Game Production Course Code: SM3608 Course Duration:
The aims of this module are to teach you how design and create graphics to represent data. In particular, to:
MODULE SPECIFICATION UNDERGRADUATE PROGRAMMES KEY FACTS Module name Data Visualization Module code IN3030 School Mathematics, Computer Science and Engineering Department or equivalent Department of Computing
ADVANCED VISUALIZATION
Cyberinfrastructure Technology Integration (CITI) Advanced Visualization Division ADVANCED VISUALIZATION Tech-Talk by Vetria L. Byrd Visualization Scientist November 05, 2013 THIS TECH TALK Will Provide
William Paterson University of New Jersey Department of Computer Science College of Science and Health Course Outline
William Paterson University of New Jersey Department of Computer Science College of Science and Health Course Outline 1. TITLE OF COURSE AND COURSE NUMBER: Computer Graphics, CS 461, Credits: 3, (Major
CPIT-285 Computer Graphics
Department of Information Technology B.S.Information Technology ABET Course Binder CPIT-85 Computer Graphics Prepared by Prof. Alhasanain Muhammad Albarhamtoushi Page of Sunday December 4 0 : PM Cover
Visualizing Repertory Grid Data for Formative Assessment
Visualizing Repertory Grid Data for Formative Assessment Kostas Pantazos 1, Ravi Vatrapu 1, 2 and Abid Hussain 1 1 Computational Social Science Laboratory (CSSL) Department of IT Management, Copenhagen
Overview of InfoVis. Exercise. Get out pencil and paper. CS 7450 - Information Visualization Aug. 19, 2015 John Stasko. Fall 2015 CS 7450 2
Overview of InfoVis CS 7450 - Information Visualization Aug. 19, 2015 John Stasko Exercise Get out pencil and paper Fall 2015 CS 7450 2 1 Data Fall 2015 CS 7450 4 2 Data Overload Confound: How to make
Tableau's data visualization software is provided through the Tableau for Teaching program.
A BEGINNER S GUIDE TO VISUALIZATION Featuring REU Site Collaborative Data Visualization Applications June 10, 2014 Vetria L. Byrd, PhD Advanced Visualization, Director REU Coordinator Visualization Scientist
COMP-557: Fundamentals of Computer Graphics McGill University, Fall 2010
COMP-557: Fundamentals of Computer Graphics McGill University, Fall 2010 Class times 2:25 PM - 3:55 PM Mondays and Wednesdays Lecture room Trottier Building 2120 Instructor Paul Kry, [email protected] Course
Visualisatie BMT. Introduction, visualization, visualization pipeline. Arjan Kok Huub van de Wetering ([email protected])
Visualisatie BMT Introduction, visualization, visualization pipeline Arjan Kok Huub van de Wetering ([email protected]) 1 Lecture overview Goal Summary Study material What is visualization Examples
Single Level Drill Down Interactive Visualization Technique for Descriptive Data Mining Results
, pp.33-40 http://dx.doi.org/10.14257/ijgdc.2014.7.4.04 Single Level Drill Down Interactive Visualization Technique for Descriptive Data Mining Results Muzammil Khan, Fida Hussain and Imran Khan Department
Hierarchy and Tree Visualization
Hierarchy and Tree Visualization Definition Hierarchies An ordering of groups in which larger groups encompass sets of smaller groups. Data repository in which cases are related to subcases Hierarchical
CSC475 Distributed and Cloud Computing Pre- or Co-requisite: CSC280
Computer Science Department http://cs.salemstate.edu CSC475 Distributed and Cloud Computing Pre- or Co-requisite: CSC280 4 cr. Instructor: TBA Office: location Phone: (978) 542-extension Email: [email protected]
Visualization Techniques in Data Mining
Tecniche di Apprendimento Automatico per Applicazioni di Data Mining Visualization Techniques in Data Mining Prof. Pier Luca Lanzi Laurea in Ingegneria Informatica Politecnico di Milano Polo di Milano
Introduction of Information Visualization and Visual Analytics. Chapter 2. Introduction and Motivation
Introduction of Information Visualization and Visual Analytics Chapter 2 Introduction and Motivation Overview! 2 Overview and Motivation! Information Visualization (InfoVis)! InfoVis Application Areas!
Visualization in 4D Construction Management Software: A Review of Standards and Guidelines
315 Visualization in 4D Construction Management Software: A Review of Standards and Guidelines Fadi Castronovo 1, Sanghoon Lee, Ph.D. 1, Dragana Nikolic, Ph.D. 2, John I. Messner, Ph.D. 1 1 Department
On History of Information Visualization
On History of Information Visualization Mária Kmeťová Department of Mathematics, Constantine the Philosopher University in Nitra, Tr. A. Hlinku 1, Nitra, Slovakia [email protected] Keywords: Abstract: abstract
Knowledge Visualization: A Comparative Study between Project Tube Maps and Gantt Charts
Knowledge Visualization: A Comparative Study between Project Tube Maps and Gantt Charts Remo Aslak Burkhard (University of St.Gallen, [email protected]) Michael Meier (vasp datatecture GmbH, [email protected])
Using Tableau for Visual Analytics in Libraries Nicole Sibley Simmons College
Using Tableau for Visual Analytics in Libraries Nicole Sibley Simmons College Using Tableau for Visual Analytics in Libraries 2 With the rise of big data, information visualization is emerging as an area
Department of Geography University of Idaho. GEOG 390: Geographic Visualization January to May 2010 COURSE OUTLINE. (subject to change)
Department of Geography University of Idaho GEOG 390: Geographic Visualization January to May 2010 COURSE OUTLINE (subject to change) Instructor Classes meet Mondays, Wednesdays 3:30 5:45 pm at MCCL 206
Introduction to Computer Graphics. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2012
CSE 167: Introduction to Computer Graphics Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2012 Today Course organization Course overview 2 Course Staff Instructor Jürgen Schulze,
Dynamic Visualization and Time
Dynamic Visualization and Time Markku Reunanen, [email protected] Introduction Edward Tufte (1997, 23) asked five questions on a visualization in his book Visual Explanations: How many? How often? Where? How
Institution : Majmaah University. Academic Department : College of Science at AzZulfi. Programme : Computer Science and Information Course :
Institution : Majmaah University. Academic Department : College of Science at AzZulfi. Programme : Computer Science and Information Course : Computer Graphics (CSI-425) Course Coordinator : Mr. ISSA ALSMADI
ICS : 435. Computer Graphics Applications. Instructor : Da'ad Albalawneh
ICS : 435 Computer Graphics Applications Instructor : Da'ad Albalawneh Course Outline Applications CAD/CAM, Art, Entertainment, Education, Training, Visualization, GUI, Image Processing. Overview of Computer
Professional Organization Checklist for the Computer Science Curriculum Updates. Association of Computing Machinery Computing Curricula 2008
Professional Organization Checklist for the Computer Science Curriculum Updates Association of Computing Machinery Computing Curricula 2008 The curriculum guidelines can be found in Appendix C of the report
COMP 150-04 Visualization. Lecture 11 Interacting with Visualizations
COMP 150-04 Visualization Lecture 11 Interacting with Visualizations Assignment 5: Maps Due Wednesday, March 17th Design a thematic map visualization Option 1: Choropleth Map Implementation in Processing
Information Visualisation and Visual Analytics for Governance and Policy Modelling
Information Visualisation and Visual Analytics for Governance and Policy Modelling Jörn Kohlhammer 1, Tobias Ruppert 1, James Davey 1, Florian Mansmann 2, Daniel Keim 2 1 Fraunhofer IGD, Fraunhoferstr.
A Short Introduction on Data Visualization. Guoning Chen
A Short Introduction on Data Visualization Guoning Chen Data is generated everywhere and everyday Age of Big Data Data in ever increasing sizes need an effective way to understand them History of Visualization
CAD and Creativity. Contents
CAD and Creativity K C Hui Department of Automation and Computer- Aided Engineering Contents Various aspects of CAD CAD training in the university and the industry Conveying fundamental concepts in CAD
DATA VISUALIZATION. Lecture 1 Introduction. Lin Lu http://vr.sdu.edu.cn/~lulin/ [email protected]
DATA VISUALIZATION Lecture 1 Introduction Lin Lu http://vr.sdu.edu.cn/~lulin/ [email protected] Visualization 可 视 化 Visualization now seen as key part of modern computing High performance computing generates
CSE841 Artificial Intelligence
CSE841 Artificial Intelligence Dept. of Computer Science and Eng., Michigan State University Fall, 2014 Course web: http://www.cse.msu.edu/~cse841/ Description: Graduate survey course in Artificial Intelligence.
Project Management (Gestão de projectos) 2013 / 2014
Project Management (Gestão de projectos) 2013 / 2014 Offered to all PhD Programs of the School of Engineering (UMinho) One Semester Course (5 ects) Runs February - July Instructors J.M.Valério de Carvalho
Information Visualization WS 2013/14 11 Visual Analytics
1 11.1 Definitions and Motivation Lot of research and papers in this emerging field: Visual Analytics: Scope and Challenges of Keim et al. Illuminating the path of Thomas and Cook 2 11.1 Definitions and
Databases. DSIC. Academic Year 2010-2011
Databases DSIC. Academic Year 2010-2011 1 Lecturer José Hernández-Orallo Office 236, 2nd floor DSIC. Email: [email protected] http://www.dsic.upv.es/~jorallo/docent/bda/bdaeng.html Attention hours On
Web Mining Seminar CSE 450. Spring 2008 MWF 11:10 12:00pm Maginnes 113
CSE 450 Web Mining Seminar Spring 2008 MWF 11:10 12:00pm Maginnes 113 Instructor: Dr. Brian D. Davison Dept. of Computer Science & Engineering Lehigh University [email protected] http://www.cse.lehigh.edu/~brian/course/webmining/
What is Visualization? Information Visualization An Overview. Information Visualization. Definitions
What is Visualization? Information Visualization An Overview Jonathan I. Maletic, Ph.D. Computer Science Kent State University Visualize/Visualization: To form a mental image or vision of [some
Introduction to WebGL
Introduction to WebGL Alain Chesnais Chief Scientist, TrendSpottr ACM Past President [email protected] http://www.linkedin.com/in/alainchesnais http://facebook.com/alain.chesnais Housekeeping If you are
Information Visualization and Visual Analytics
Information Visualization and Visual Analytics Pekka Wartiainen University of Jyväskylä [email protected] 23.4.2014 Outline Objectives Introduction Visual Analytics Information Visualization Our
Assessing Learners Behavior by Monitoring Online Tests through Data Visualization
International Journal of Electronics and Computer Science Engineering 2068 Available Online at www.ijecse.org ISSN : 2277-1956 Assessing Learners Behavior by Monitoring Online Tests through Data Visualization
Interactive Visual Data Analysis in the Times of Big Data
Interactive Visual Data Analysis in the Times of Big Data Cagatay Turkay * gicentre, City University London Who? Lecturer (Asst. Prof.) in Applied Data Science Started December 2013 @ the gicentre (gicentre.net)
Stage III courses COMPSCI 314
Stage III courses To major in Computer Science, you have to take four Stage III COMPSCI courses, plus one other Stage III course chosen from the BSc Schedule. This may be another Stage III COMPSCI course.
COGNITIVE SCIENCE 222
Minds, Brains, & Intelligent Behavior: An Introduction to Cognitive Science Bronfman 106, Tuesdays and Thursdays, 9:55 to 11:10 AM Williams College, Spring 2007 INSTRUCTOR CONTACT INFORMATION Andrea Danyluk
Business Intelligence in E-Learning
Business Intelligence in E-Learning (Case Study of Iran University of Science and Technology) Mohammad Hassan Falakmasir 1, Jafar Habibi 2, Shahrouz Moaven 1, Hassan Abolhassani 2 Department of Computer
COMPUTER GRAPHICS Computer Graphics
COMPUTER GRAPHICS Computer Graphics involves display, manipulation and storage of pictures and experimental data for proper visualization using a computer. Typical graphics system comprises of a host computer
Carleton University School of Computer Science COMP 3009 - Computer graphics Fall 2015
Carleton University School of Computer Science COMP 3009 - Computer graphics Fall 2015 Class Schedule Classroom HP4125 Class Time Tuesday and Thursday 16:00-18:00 Curese Website Information is on CULearn
CS 325 Computer Graphics
CS 325 Computer Graphics 01 / 25 / 2016 Instructor: Michael Eckmann Today s Topics Review the syllabus Review course policies Color CIE system chromaticity diagram color gamut, complementary colors, dominant
How To Create A Data Visualization
CSCI 552 Data Visualization Shiaofen Fang What Is Visualization? We observe and draw conclusions A picture says more than a thousand words/numbers Seeing is believing, seeing is understanding Beware of
USING SELF-ORGANIZING MAPS FOR INFORMATION VISUALIZATION AND KNOWLEDGE DISCOVERY IN COMPLEX GEOSPATIAL DATASETS
USING SELF-ORGANIZING MAPS FOR INFORMATION VISUALIZATION AND KNOWLEDGE DISCOVERY IN COMPLEX GEOSPATIAL DATASETS Koua, E.L. International Institute for Geo-Information Science and Earth Observation (ITC).
Interactive Information Visualization of Trend Information
Interactive Information Visualization of Trend Information Yasufumi Takama Takashi Yamada Tokyo Metropolitan University 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan [email protected] Abstract This paper
MEng, BSc Computer Science with Artificial Intelligence
School of Computing FACULTY OF ENGINEERING MEng, BSc Computer Science with Artificial Intelligence Year 1 COMP1212 Computer Processor Effective programming depends on understanding not only how to give
Visualization Techniques for Data Mining in Business Context: A Comparative Analysis
Visualization Techniques for Data Mining in Business Context: A Comparative Analysis Ralph K. Yeh University of Texas at Arlington Box 19437, Arlington, TX 76019 817-272-3707 Fax: (817) 272-5801 E-mail:
CS 207 - Data Science and Visualization Spring 2016
CS 207 - Data Science and Visualization Spring 2016 Professor: Sorelle Friedler [email protected] An introduction to techniques for the automated and human-assisted analysis of data sets. These
Communication Networks MAP-TELE 2012/13
Communication Networks MAP-TELE 2012/13 Objective of the course The main objective of the course is to present the fundamentals of modern communication systems and networks and allow students to consolidate
Visualization methods for patent data
Visualization methods for patent data Treparel 2013 Dr. Anton Heijs (CTO & Founder) Delft, The Netherlands Introduction Treparel can provide advanced visualizations for patent data. This document describes
DATA MINING TECHNOLOGY. Keywords: data mining, data warehouse, knowledge discovery, OLAP, OLAM.
DATA MINING TECHNOLOGY Georgiana Marin 1 Abstract In terms of data processing, classical statistical models are restrictive; it requires hypotheses, the knowledge and experience of specialists, equations,
CSE 571S: Network Security CSE571S
CSE 571S: Network Security Raj Jain Washington University in Saint Louis Saint Louis, MO 63130 [email protected] These slides are available on-line at: http://www.cse.wustl.edu/~jain/cse571-07/ 1-1 Overview!
MEng, BSc Applied Computer Science
School of Computing FACULTY OF ENGINEERING MEng, BSc Applied Computer Science Year 1 COMP1212 Computer Processor Effective programming depends on understanding not only how to give a machine instructions
Computer Graphics AACHEN AACHEN AACHEN AACHEN. Public Perception of CG. Computer Graphics Research. Methodological Approaches - - - - - - - - - -
Public Perception of CG Games Computer Graphics Movies Computer Graphics Research algorithms & data structures fundamental continuous & discrete mathematics optimization schemes 3D reconstruction global
CS 4810 Introduction to Computer Graphics
CS 4810 Introduction to Computer Graphics Connelly Barnes University of Virginia Acknowledgement: slides by Jason Lawrence, Misha Kazhdan, Allison Klein, Tom Funkhouser, Adam Finkelstein and David Dobkin
INFS5991 BUSINESS INTELLIGENCE METHODS. Course Outline Semester 1, 2015
Business School School of Information Systems, Technology and Management INFS5991 BUSINESS INTELLIGENCE METHODS Course Outline Semester 1, 2015 Part A: Course-Specific Information Please consult Part B
Visualization Criticism The Missing Link Between Information Visualization and Art
Visualization Criticism The Missing Link Between Information Visualization and Art Robert Kosara The University of North Carolina at Charlotte [email protected] Abstract Classifications of visualization
Computational Science and Informatics (Data Science) Programs at GMU
Computational Science and Informatics (Data Science) Programs at GMU Kirk Borne George Mason University School of Physics, Astronomy, & Computational Sciences http://spacs.gmu.edu/ Outline Graduate Program
Job list - Research China
Job list - Research China Job # Job Title Page 010499 Scientist for Mechanical Engineering P2-3 002590 Senior Scientist for Biomedical Engineering P4-5 022831 Research Scientist for MRI P6-7 010501 Scientist
Applied Communication. Introduction to Professional Communication
Copyright Kwantlen Polytechnic University Department: Applied Communication Course Acronym and Number: CMNS 1140 Former Acronym and Number: Credits: 3 Descriptive Title: Introduction to Professional Communication
TIES443. Lecture 9: Visualization. Lecture 9. Course webpage: http://www.cs.jyu.fi/~mpechen/ties443. November 17, 2006
TIES443 Lecture 9 Visualization Mykola Pechenizkiy Course webpage: http://www.cs.jyu.fi/~mpechen/ties443 Department of Mathematical Information Technology University of Jyväskylä November 17, 2006 1 Topics
TEXTURE AND BUMP MAPPING
Department of Applied Mathematics and Computational Sciences University of Cantabria UC-CAGD Group COMPUTER-AIDED GEOMETRIC DESIGN AND COMPUTER GRAPHICS: TEXTURE AND BUMP MAPPING Andrés Iglesias e-mail:
Instructor. Goals. Image Synthesis Examples. Applications. Computer Graphics. Why Study 3D Computer Graphics?
Computer Graphics Motivation: Why do we study 3D Graphics? http://www.cs.ucsd.edu/~ravir Instructor http://www.cs.ucsd.edu/~ravir PhD Stanford, 2002. PhD thesis developed Spherical Harmonic Lighting widely
DPLS 722 Quantitative Data Analysis
DPLS 722 Quantitative Data Analysis Spring 2011 3 Credits Catalog Description Quantitative data analyses require the use of statistics (descriptive and inferential) to summarize data collected, to make
