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VITA for links and nodes analysis network analysis for counterror & intelligence Zachary Jacobson, Health Canada with Ben Houston and Olivier Dagenais,

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Presentation on theme: "VITA for links and nodes analysis network analysis for counterror & intelligence Zachary Jacobson, Health Canada with Ben Houston and Olivier Dagenais,"— Presentation transcript:

1 VITA for links and nodes analysis network analysis for counterror & intelligence Zachary Jacobson, Health Canada with Ben Houston and Olivier Dagenais, Carleton University March 2003

2 VITA - a visual front end for document search systems to discover relationships among elements and reducing search complexity control by the user results presentation under user control Intended to be engine independent Various prototypes

3 VITA- Concept

4 VITA Prototypes VITA-  Initial concept version. No longer extant VITA-  (NetViz) Written in C++ "Crown of Thorns" display Worked with InQuisit search engine VITA-  (AutoViz) Written in C++ Interfaced to Autonomy search engine NetViz and AutoViz only exist in demo form

5 VITA-  (NetViz) Example

6 VITA-  (AutoViz) Example

7 Gravity

8 Filtering VITA-  (AutoViz) Example

9 VITA-  Example

10 VITA Prototypes (cont.) VITA-  Written in Visual Basic ++ Research testbed for visual and control side  Parametrically configurable at run time  Default settings Interfaced to multiple search engines  Approx. 2 days effort to interface a new search engine VITA-  Written in C++ Based on capabilities of VITA-  Faster, more robust than VITA-  Removes 3rd party software dependencies of VITA-  Modular construction  Incomplete but still usable with limited clustering and handling

11 VITA-  Example

12 VITA -  Example

13 Originally [web] search and KM But the gravity can cluster and group other items. N.B. the quantized use of the 3 rd dimension [height above the floor]

14 3 fixed planes 3 fixed planes Concepts web pages Extracts VITA General Layout Mechanism

15 Quantized 3 rd dimension—say— For a collection of suspect emails about something perhaps quite innocuous. “To” level “From” level Body level Traffic analysis should ID cells of activity Perhaps identify a single text thread

16 Other possible floorings Time [datestamp] level To-from level Keyword level

17 Or, network protection From To Sites

18 Common Fate Who’s attached most strongly to whom? Who’s pinging whom? Who’s pinging many? Or, who’s being pinged by many?


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