0000000000138928
AUTHOR
Jerome H. Friedman
Panel Discussion: Systems for Data Analysis What they AEE; what they Could be?
CRANE: I’d like to pose a couple of questions: (1) Command Languages — A tool for the astronomer or for the programmer? (2) Portability — Holy Cow or Red Herring? I propose that we start with the first one and see how far we get. If we don’t get past that, fine. If we get on to the question of portability, this is also fine. Let me just open up the discussion by asking Rudi Albrecht to make a comment.
Panel Discussion on “ how can Computer Science Contribute to the Solution of Problems Posed by Astronomers ?”
A Panel was hold on June 3rd summarizing, in a way, the guide- lines and the aims of the Workshop. General questionswere addressed to M.Disney, E.Groth and D.Wells, who have expressed in the Workshop the point of view from Astronomy in the Sections “Data Analysis methodologies”, “Image processing” and “Systems for Data Analysis” respectively:
Panel Discussion on Data Analysis Trends in X-Ray and γ-Ray Astronomy 30/5/84, 11°°–12°°
[The text of the panel has been edited by Dr. ozel (with indispensable help from Gabi Breuer, secretary of MPIfR) from a tape recording. The words not completely understandable are noted by (?), while various inclusions for the continuity of the text are indicated by [ ]. The slides and viewgraphs presented in the panel are added as Figures and Tables.]
Intruder Pattern Identification
This paper considers the problem of intrusion detection in information systems as a classification problem. In particular the case of masquerader is treated. This kind of intrusion is one of the more difficult to discover because it may attack already open user sessions. Moreover, this problem is complex because of the large variability of user models and the lack of available data for the learning purpose. Here, flexible and robust similarity measures, suitable also for non-numeric data, are defined, they will be incorporated on a one-class training K N N and compared with several classification methods proposed in the literature using the Masquerading User Data set (www.schonlau.net) repr…
New Similarity Rules for Mining Data
Variability and noise in data-sets entries make hard the discover of important regularities among association rules in mining problems. The need exists for defining flexible and robust similarity measures between association rules. This paper introduces a new class of similarity functions, SF's, that can be used to discover properties in the feature space X and to perform their grouping with standard clustering techniques. Properties of the proposed SF's are investigated and experiments on simulated data-sets are also shown to evaluate the grouping performance.
Panel Discussion on Data Analysis Trends in X-Ray and Gamma-Ray Astronomy
ZIMMERMANN: Let me begin the panel discussion on Data Analysis Trends in X-ray and Gamma-ray astronomy by first introducing the panel members. These are from the left to the right: Roland Diehl, Ethan Schreier, Rosolino Buccheri, Livio Scarsi, Jean-Marc Chassery and Wolfgang Voges. With the exception of Jean-Marc Chassery, who is an expert on image processing and statistical analysis, all the others have longer experience in the X-ray and Gamma-ray fields. May I ask the speakers to keep their contributions to not more than five minutes, in order to allow ample room for discussion with the audience.
Panel Discussion on Trends in Optical and Radio Data Analysis
Albrecht: What I want to do is to give a brief five-minute introduction to the subject, justifying the title which puts optical and radio astronomy in one and the same category, which I believe it is, as far as data analysis is concerned, and then I will ask the panel members to give us two-minute statements of their opinions on the subject and then I would like to ask the audience to fire questions at us.