The role of metadata in entity recognition.

1. Metadata Visualization:
Metamorphosis of Entity Recognition
Dr. Tabin Hasan
Assistant Professor
American International University – Bangladesh
October 2010

2. Information Visualization
• Some Areas
– Textual information
– Temporal data
– Spatial Data
– Spatio-temporal data
– Numeric Data
– Graph
– And even more…

3. Remember
• Information Visualization is not UI Design
• Information Visualization at the concerns also
– Information representation
– Navigation through information space

4. Contents
• Visual Metadata that speaks itself
– Level of visual properties
– Elements of visual properties
– How much detail is sufficient
– When it lies!
• Textual Metadata Visualization
– Is it weird? Necessity of information feed
– How much is sufficient to identify an entity
– What are the most important ones?
– In which order they makes sense
• Visual and textual in combination
• Discussion
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion

5. Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Level of visual properties
Elements of visual properties
How much detail is sufficient
When it lies!

6. Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Level of visual properties
Elements of visual properties
How much detail is sufficient
When it lies!

7. Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Level of visual properties
Elements of visual properties
How much detail is sufficient
When it lies!

8. Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Level of visual properties
Elements of visual properties
How much detail is sufficient
When it lies!

9. Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Is it weird? Necessity of information feed
How much is sufficient to identify an entity
What are the most important ones?
In which order they makes sense

10. Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Is it weird? Necessity of information feed
How much is sufficient to identify an entity
What are the most important ones?
In which order they makes sense

11. Albert Einstein
Nobel Prize in Physics
"name";"Einstein on socialism"
"name";"God does not play dice"
"name";"Alber Enstien"
"name";"Al Einstein"
"name";"Albert Einstein"
"name";"Ejnstejno"
"name";"Einsteinian"
"name";"Albert Einstin"
"name";"Albert Einstein's"
"name";"Einsetein"
"name";"Einstien"
"name";"Albert Enstein"
"name";"Albert LaFache Einstein"
"name";"Einstien"
"name";"Albert Einstein"
"source";"YAGO"
"prize";"Nobel Prize in Physics"
"date of birth";"1879-03-14"
"date of death";"1955-04-18"
"birthplace";"Ulm"
"birthplace";"Free Imperial City of Ulm"
"birthplace";"Ulm displaced persons camp"
"child";"Hans Albert Einstein"
"child";"Hans Einstein"
"child";"Lieserl Einstein"
"child";"Eduard Einstein"
"spouse";"Elsa Einstein"
"spouse";"Elsa Löwenthal"
"nationality";"Kingdom of Württemberg"
"nationality";"Kingdom of Wirtemberg"
"nationality";"Kingdom of Wuerttemberg"
"nationality";"Würtemberg"
"nationality";"Kingdom of Wurttemberg"
"influence";"Rudolf Carnap"
"influence";"Rudolph Carnap"
"influence";"Carnap"
"influence";"R. Carnap"
"influence";"Boris Podolsky"
"influence";"Борис Подольский"
"influence";"Boris Podolski"
"influence";"Théophile de Donder"
"influence";"Théophile Donder"
"influence";"Theophile De Donder"
"influence";"Theophile de Donder"
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Is it weird? Necessity of information feed
How much is sufficient to identify an entity
What are the most important ones?
In which order they makes sense

12. • Make
• NIKON CORPORATION
• Model
• NIKON D90
• Orientation
• 0
• X Resolution
• 72 dots per inch
• Y Resolution
• 72 dots per inch
• Resolution Unit
• Inch
• Software
• Picasa 3.0
• Date/Time
• 2010:05:25 22:53:43
• YCbCr Positioning
• Center of pixel array
• Reference Black/White
• [0,0,0] [255,255,255]
• Exposure Time
• 1/400 sec
• F-Number
• F9
• Exposure Program
• Aperture priority
• ISO Speed Ratings
• 400
• Exif Version
• 2.20
• Date/Time Original
• 2010:05:01 17:43:53
• Date/Time Digitized
• 2010:05:01 17:43:53
• Components Configuration
• YCbCr
• Exposure Bias Value
• 0 EV
• Max Aperture Value
• F5.1
• Metering Mode
• Multi-segment
• Light Source
• Unknown
• Flash
• Flash did not fire
• Focal Length
• 80.0 mm
• User Comment
• Sub-Sec Time
• 00
• Sub-Sec Time Original
• 00
• Sub-Sec Time Digitized
• 00
• FlashPix Version
• 1.00
• Color Space
• Undefined
• Exif Image Width
• 4288 pixels
• Exif Image Height
• 2848 pixels
• Sensing Method
• One-chip color area sensor
• File Source
• Digital Still Camera (DSC)
• Scene Type
• Directly photographed image
• CFA Pattern
• 0 2 0 2 1 2 0 1
• Custom Rendered
• Normal process
• Exposure Mode
• Auto exposure
• White Balance
• Auto white balance
• Digital Zoom Ratio
• 1
• Focal Length 35
• 120mm
• Scene Capture Type
• Standard
• Gain Control
• Low gain up
• Contrast
• None
• Saturation
• None
• Sharpness
• None
• Subject Distance Range
• Unknown
• Compression
• JPEG (old-style)
• Thumbnail Offset
• 10912 bytes
• Thumbnail Length
• 6090 bytes
• Thumbnail Data
• [6090 bytes of thumbnail data]
• Firmware Version
• 2.10
• ISO
• ISO 400
• Quality & File Format
• RAW
• White Balance
• AUTO
• AF Type
• AF-A
• White Balance Fine
• 0 0
• White Balance RB Coefficients
• 178515625/100000000 139453125/100000000 1/1 1/1
• Unknown 01
• 0 1 6 0
• Unknown 02
• 0 1 12 0
• Unknown 03
• 9694
• ISO
• 0 400
• Unknown 24
• 0
• Unknown 04
• 14
• Lens
• 18-200mm f/3.5-5.6
• Unknown 05
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• OFF
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• Unknown 14
• 2176 1434
• Unknown 26
• 3582651
• Unknown 27
• 0
• Exposure Sequence Number
• 553
• Unknown 30
• Unknown 16
• 9788
• Interoperability Index
• Recommended Exif Interoperability Rules (ExifR98)
• Interoperability Version
• .
• GPS Version ID
• 0 0 2 2
• GPS Latitude Ref
• N
• GPS Latitude
• 46"4'2.9489136
• GPS Longitude Ref
• E
• GPS Longitude
• 11"9'30.461657
• GPS Altitude Ref
• Sea level
• GPS Altitude
• 0 metres
• Data Precision
• 8 bits
• Image Height
• 2848 pixels
• Image Width
• 4288 pixels
• Number of Components
• 3
• Component 1
• Y component: Quantization table 0, Sampling factors 1 horiz/1 vert
• Component 2
• Cb component: Quantization table 1, Sampling factors 1 horiz/1 vert
• Component 3
• Cr component: Quantization table 1, Sampling factors 1 horiz/1 vert
Make: NIKON CORPORATION
Model: NIKON D90
Orientation: 0X
Resolution: 72 dots per inch
Y Resolution: 72 dots per inch
Resolution Unit: Inch
Software: Picasa 3.0
Date/Time: 2010:05:25 22:53:43
YCbCr Positioning: Center of pixel array
Reference Black/White: [0,0,0] [255,255,255]
Exposure Time: 1/400 sec
Image Height: 2848 pixels
Image Width: 4288 pixels
Number of Components: 3
Component 1
Y component: Quantization table 0, Sampling factors 1 horiz/1 vert
Component 2
Cb component: Quantization table 1, Sampling factors 1 horiz/1 vert
Component 3
Cr component: Quantization table 1, Sampling factors 1 horiz/1 vert
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Is it weird? Necessity of information feed
How much is sufficient to identify an entity
What are the most important ones?
In which order they makes sense

13. Or simply
PhD Dinner
2010
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Is it weird? Necessity of information feed
How much is sufficient to identify an entity
What are the most important ones?
In which order they makes sense

14. It depends how things are remembered
And of course who is asking…
It depends on type of entity
Portrait of a Musician
Leonardo da Vinci
Mona Lisa
Leonardo da Vinci
Carl Marx
Das Capital
Communism
Replica for sale: $500
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Is it weird? Necessity of information feed
How much is sufficient to identify an entity
What are the most important ones?
In which order they makes sense

15. • Again it depends on context
• A name label is the first thing people would try to
remember
Example “Book”
Writer: Jack London
Title: Call of the Wild
Location: America
Published in: 1903
Type: Novel
Publisher: Macmillan
Title: Call of the Wild
Writer: Jack London
Published in: 1903
Location: America
Type: Novel
Publisher: Macmillan
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion
Is it weird? Necessity of information feed
How much is sufficient to identify an entity
What are the most important one?
In which order they makes sense

16. Albert Einstein
Nobel Prize in Physics
User needs to be
informed what we are
talking about, Theory of
relativity or the person?
Satyendra Nath Bose
Physicist
An image with a name label is worth of a million words
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion

17. Marco
Marco Marco Marco Marco Marco Marco
Trento Trento Milam Palermo Trento Verona
ABC spa c&m
consulting
Ltd.
Mandelli UNITN UNITN Ferrament
a Alcofer
S.R.L.
Perhaps job position required
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion

18. A Facebook case
Tagging a person Why all these concerns?
• Saving Visual space
• Faster Visual recognition
• Reduced cognitive load
• Reduced error and effort
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion

19. Thanks for the participation
Visual Metadata that speaks itself
Textual Metadata Visualization
Visual and textual in combination
Discussion