Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television...
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![Page 1: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/1.jpg)
Reading Metadata
Between the Lines:
Searching for
Stories, People, Places and More
in Television News
Kai Chan
Social Sciences Computing
University of California, Los Angeles
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What?
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What We Do with Television News
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Make Metadata Searchable
![Page 5: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/5.jpg)
Make Metadata Searchable
captionTHESE RECALLED CARS ARE AMONG
THE MOST POPULAR FOR THE PAST 12
YEARS.
![Page 6: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/6.jpg)
Make Metadata Searchable
caption(searchable)
THESE RECALLED CARS ARE AMONG
THE MOST POPULAR FOR THE PAST 12
YEARS.
![Page 7: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/7.jpg)
Make Metadata Searchable
metadata
caption(searchable)
THESE RECALLED CARS ARE AMONG
THE MOST POPULAR FOR THE PAST 12
YEARS.
![Page 8: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/8.jpg)
Make Metadata Searchable
metadata(not searchable)
caption(searchable)
THESE RECALLED CARS ARE AMONG
THE MOST POPULAR FOR THE PAST 12
YEARS.
![Page 9: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/9.jpg)
Story Segment
Story 1 Story 2
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Story Segment
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Name Entity
Name: John McCainRole: US SenatorParty: Republican
Name: Greta Van SusterenRole: AnchorNetwork: Fox News Channel
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Name Entity
NJ Governor: cooperation from US President “outstanding”, “deserves great credit”
Republican Democrat praise (!)
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Non-Verbal Communication
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Non-Verbal Communication
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On-Screen Text
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On-Screen Text
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How?
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1. Help Users Search
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Define Metadata Structure
Tag Attribute Name: Value
Attribute Name: Value
Attribute Name: Value
Start Time End Time
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Define Metadata Structure
SEG Type: Headline
Topic: Ebola Scare
Country: US
1:00:00 1:03:00
(story segment)
start time end time tag attributes
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Search in Multiple Places
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Offer Suggestions
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2. Make the Search Happen
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Map to Documents and Fields
SEG_Topic: Ebola Scare
NER_Name: John McCain
NER_Role: Senator
fields
SEG_Type: Headline
(program info, caption)
document
NER_State: Arizona
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Map to Documents and Fields
SEG_Topic: Ebola Scare
NER_Name: John McCain
NER_Role: Senator
fields
SEG_Type: Headline
(program info, caption)
document
NER_State: Arizona
NER_Name: John Chiang
NER_Role: Controller
NER_State: California
SEG_Topic: Drought
SEG_Type: Politics
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Define Semantics
+TEXT_Text:“drought”
+NER_Role:“Senator”
+NER_State:“California”
Query:
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Define Semantics
Interpretation 1:
“drought”
time
start end
Role: Senator State: California
start end
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Define Semantics
Interpretation 2:
“drought”
time
start end start end
“drought”
Role: Senator State: California
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Define Semantics
Interpretation 3:
“drought”
time
start end
Role: Senator
State: California
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Define Semantics
Interpretation 4:
“drought”
time
start end
Role: Senator
State: California
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Map to Documents and Fields
SEG_Topic: Ebola Scare
NER_Name: John McCain
NER_Role: Senator
fields
SEG_Type: Headline
(program info, caption)
document
NER_State: Arizona
NER_Name: John Chiang
NER_Role: Controller
NER_State: California
SEG_Topic: Drought
SEG_Type: Politics
![Page 32: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/32.jpg)
Map to Documents and Fields
SEG_Topic: Ebola Scare
NER_Name: John McCain
NER_Role: Senator
fields
SEG_Type: Headline
(program info, caption)
document
NER_State: Arizona
NER_Name: John Chiang
NER_Role: Controller
NER_State: California
SEG_Topic: Drought
SEG_Type: Politics
![Page 33: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/33.jpg)
Map to Documents and Fields
SEG_Topic: Ebola Scare
NER_Name: John McCain
NER_Role: Senator
fields
SEG_Type: Headline
(program info, caption)
document
NER_State: Arizona
NER_Name: John Chiang
NER_Role: Controller
NER_State: California
SEG_Topic: Drought
SEG_Type: Politics
![Page 34: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/34.jpg)
Map to Documents and Fields
SEG_Topic: Ebola Scare
NER_Name: John McCain
NER_Role: Senator
fields
SEG_Type: Headline
(program info, caption)
document
NER_State: Arizona
NER_Name: John Chiang
NER_Role: Controller
NER_State: California
SEG_Topic: Drought
SEG_Type: Politics
![Page 35: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/35.jpg)
Map to Documents and Fields
SEG_Topic: Ebola Scare
NER_Name: John McCain
NER_Role: Senator
fields
SEG_Type: Headline
(program info, caption)
document
NER_State: Arizona
NER_Name: John Chiang
NER_Role: Controller
NER_State: California
SEG_Topic: Drought
SEG_Type: Politics
![Page 36: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/36.jpg)
Map to Documents and Fields
SEG_Topic: Ebola Scare
NER_Name: John McCain
NER_Role: Senator
fields
SEG_Type: Headline
(program info, caption)
document
NER_State: Arizona
NER_Name: John Chiang
NER_Role: Controller
NER_State: California
SEG_Topic: Drought
SEG_Type: Politics
![Page 37: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/37.jpg)
Map to Documents and Fields
SEG_Topic: Ebola Scare
NER_Name: John McCain
NER_Role: Senator
fields
SEG_Type: Headline
(program info, caption)
document
NER_State: Arizona
NER_Name: John Chiang
NER_Role: Controller
NER_State: California
SEG_Topic: Drought
SEG_Type: Politics
![Page 38: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/38.jpg)
3. Make the Search Meaningful
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Two Levels of Document
programdocument
tag document
tag document
tag document
1 document= 1 metadata instance
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Two Levels of Document
programdocument
tag document
tag document
tag document
1 document= 1 news program
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Two Levels of Document
programdocument
tag document
tag document
tag document
1. search metadata content
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Two Levels of Document
programdocument
tag document
tag document
tag document
2. lookup program document(s)
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Two Levels of Document
programdocument
tag document
tag document
tag document
3. filter by program information
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Two Levels of Document
NER_Role: Senator
NER_State: Arizona
tag document
NER_Role: Senator
tag document tag document
Tag: NER
NER_State: California
Tag: NER Tag: NER
NER_Role: Controller
NER_State: California
matchNOT match NOT match
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Two Levels of Document
Date
Network
Show
program document
NER_Role: Senator
tag document
Tag: NER
NER_State: California
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Filter by Metadata Boundaries
“drought”
time
start end
“drought”“drought”
Role: Governor
State: California
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Filter by Metadata Boundaries
...
EMERGENCY PLED TO THE STATE
OF CALIFORNIA IN MAY TO
CONSERVE WATER.
>> THIS DROUGHT IS A BIG
WAKE-UP CALL, A REMINDER.
THE COUPLE SAYS
THAT THEY NEED NO
REMINDERS.
...
36:18
36:22 36:18 – 36:22Tag: NERName: Jerry BrownRole: GovernorState: California
36:19
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4. Make the Search More Powerful
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Proximity Search – Word as Unit
...
>> THIS DROUGHT IS A BIG
WAKE-UP CALL, A REMINDER.
THE COUPLE SAYS
THAT THEY NEED NO
REMINDERS
THEY DO ADMIT THAT THEIR
LAWN HAS BECOME A BIT
UNSIGHTLY.
...
position 100
position 121
20 words
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Proximity Search – Time as Unit
...
>> THIS DROUGHT IS A BIG
WAKE-UP CALL, A REMINDER.
THE COUPLE SAYS
THAT THEY NEED NO
REMINDERS
THEY DO ADMIT THAT THEIR
LAWN HAS BECOME A BIT
UNSIGHTLY.
...
36:19
36:25
6 s
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Make Metadata Searchable
metadata(not searchable)
caption(searchable)
THESE RECALLED CARS ARE AMONG
THE MOST POPULAR FOR THE PAST 12
YEARS.
![Page 52: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/52.jpg)
Make Metadata Searchable – Accomplished
metadata(now searchable)
caption(searchable)
THESE RECALLED CARS ARE AMONG
THE MOST POPULAR FOR THE PAST 12
YEARS.
![Page 53: Reading Metadata between the Lines: Searching for Stories, People, Places and More in Television News](https://reader035.fdocuments.in/reader035/viewer/2022081404/559447a31a28ab0f0d8b463c/html5/thumbnails/53.jpg)
Thank you for coming!
Questions or comments?My e-mail: [email protected]
Slides available at:http://bit.ly/lsr2014tvnews(or scan this barcode)
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