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July 17, 2013
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July 22-25, 2013
The 2013 World Congress in Computer Science, Computer Engineering, and Applied Computing

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WORLDCOMP'13 Keynote Lecture - Prof. Alfred Inselberg

Last modified 2013-07-07 17:56

Visualization and Data Mining for High Dimensional Datasets
Prof. Alfred Inselberg
School of Mathematical Sciences, Tel Aviv University, Israel
Senior Fellow, San Diego Supercomputing Center
Inventor of the multidimensional system of Parallel Coordinates and author of textbook
"Parallel Coordinates: VISUAL Multidimensional Geometry", (praised by Stephen Hawking among others.)

Date: July 22, 2013
Time: 09:55 - 10:50am
Location: Tropicana Theater


    A dataset with M items has 2M subsets anyone of which may be the one satisfying our objectives. With a good data display and interactivity our fantastic pattern-recognition can not only cut great swaths searching through this combinatorial explosion, but also extract insights from the visual patterns. These are the core reasons for data visualization. With parallel coordinates the search for relations in multivariate datasets is transformed into a 2-D pattern recognition problem. Guidelines and strategies for knowledge discovery are illustrated on several real datasets (financial, process control, credit-score, intrusion-detection, one with hundreds of variables). A geometric classification algorithm is presented and applied to complex datasets. It has low computational complexity providing the classification rule explicitly and visually. The minimal set of variables (features) required to state the rules is found and ordered by their predictive value. Multivariate relations can be modeled as hypersurfaces and used for decision support. A model of a (real) country’s economy reveals sensitivities, impact of constraints, trade-offs and economic sectors unknowingly competing for the same resources. An overview of the methodology provides foundational understanding; learning the patterns corresponding to various multivariate relations. These patterns are robust in the presence of errors and that is good news for the applications.

    The parallel coordinates methodology has been applied to collision avoidance and conflict resolution algorithms for air traffic control (3 USA patents), computer vision (1 USA patent), data mining (1 USA patent), optimization, decision support and elsewhere.

    Alfred Inselberg – Parallel Coordinates — EYE-CANDY


    Prof. Inselberg received a Ph. D. in Mathematics and Physics from the University of Illinois (Champaign-Urbana) in 1965 and stayed on Research Professor until 1966. He held senior research positions at IBM, where he developed a Mathematical Model of Ear (TIME Nov. 74), concurrently having joint appointments at UCLA, USC, Technion and Ben Gurion University. Since 1995 he is Professor at the School of Mathematical Sciences of Tel Aviv University. AI was elected Senior Fellow at the San Diego Supercomputing Center in 1996 and Distinguished Visiting Professor at Korea University in Seoul in 2008, and National University of Singapore 2011. AI invented and developed the multidimensional system of Parallel Coordinates for which he received numerous awards and patents (on Air Traffic Control, Collision-Avoidance, Computer Vision, Data Mining). His textbook on "Parallel Coordinates: VISUAL Multidimensional Geometry", Springer 2009, was praised by Stephen Hawking among many others.

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