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Document Visualization at UMBC Penny Rheingans October 2002
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Document Visualization at UMBC

Jan 08, 2016

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Document Visualization at UMBC. Penny Rheingans October 2002. Goals. Provide powerful and flexible visual representations of document data in order to facilitate exploration and explanation - PowerPoint PPT Presentation
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Page 1: Document Visualization  at UMBC

Document Visualization at UMBC

Penny Rheingans

October 2002

Page 2: Document Visualization  at UMBC

Goals

• Provide powerful and flexible visual representations of document data in order to facilitate exploration and explanation

• Develop novel information visualization and interaction techniques applicable to a wide range of document types

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Document Metadata

• Date• Relevance

– multiple measures

• Topic– multiple keywords

• Provenance• Whatever

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Information Visualization Toolkit

• Glyph-based visualization of document by metadata– Glyph per document– Metadata values mapped interactively to

• 3D position• Color• Size• Opacity

• Interactive 3D viewing• Built on vtk with tcl/tk interface

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Recent Advances

• Implemented on both irix and linux platforms• Automatic and flexible scaling• Basic clustering

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Ongoing Efforts

• Additional platforms• Performance enhancements• Picking and probing• Dynamic update• Closer integration with IR engines• Application to intrusion detection

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New Directions for ivtk

• Additional visualization techniques, possibly– Additional dimension reduction methods– Parallel coordinates

• Improved user interface with expanded interaction modes (carried out as part of LUCITE task)

• Address issues of scale– Provide both context and detail on demand– Filtering of data items– Generalization and summary representations– Glyphs for composite objects– Hierarchical viewing modes (LUCITE)

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Filtering of Data Items

• Select which individual items to show– Drastically reduce number of items displayed

– Subsetting mechanisms

• Interactive value-based selection

• Stochastic sampling

• Select how to show individual items– Direct attention to match interest

– Modulate appearance of items

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Emphasis Filter Approach

• Treat match to target as variable• Map to perceptually-based parameter or alter base

mapping• Interaction capabilities

– dynamic control of view

– dynamic control of some visualization parameters

• Previous SFA-based prototype

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Personal Profiles

• Individual weightings for documents– flexible

– audience-specific

– interactive

• Supplement to precomputed relevance– simple measures

– computed dynamically

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Matching Mechanisms

• Value Requirement• Composite

– multiple factors– fuzzy matches

• Threshold– significance levels

• Window– focus area

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Future Directions in Filtering

• Revive prototype• Extend to include profile mechanism

– profile construction and manipulation

– matching metric specification

• Integrate with ivtk

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Summary Representations

• Convey overview of corpus structure without showing each individual document

• Possibilities– Visualization processes to create and render aggregates

• Splatting or other implicit representations

• Isosurfaces or volume rendering

– Explicit analysis to characterize structure

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Glyphs for Composite Objects

• Extend glyph representation to apply to composite objects– Collections

– Clusters

• Information of interest about composites– Mean variable value

– Variable range/variability

– Number of component objects

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Composite Metaphors

• Display mean and variability information in consistent manner– Position

– Color

• Some visual attributes dedicated to supporting other display parameters– Opacity

– Shape

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