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SmartNews : Semantic Searching of News Video

SmartNews : Semantic Searching of News Video. Stephen Lynn Brigham Young University CS 652. Background. Over 2000 News Stations in US 10 Broadcasts a Day About 15 Stories per Broadcast 150 Stories per day per Broadcaster Many redundant Over 300,000 Stories a Day Even more redundancy.

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SmartNews : Semantic Searching of News Video

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  1. SmartNews: Semantic Searching of News Video Stephen Lynn Brigham Young University CS 652

  2. Background • Over 2000 News Stations in US • 10 Broadcasts a Day • About 15 Stories per Broadcast • 150 Stories per day per Broadcaster • Many redundant • Over 300,000 Stories a Day • Even more redundancy

  3. Interactive News • User in Control • Only Watch Stories of Interest • Dig in to Stories Problem: How do I find background stories related to some current event?

  4. SmartNews • Semantically Enriched Search Interface • Extraction Ontology • Retrieve Past News Stories • RDF Repository • Sensitive to Inter-story Relationships • Simple Search Mechanism

  5. Example U.S. President Barack Obama visited Iraq Monday in a stop that was overshadowed by the question of when U.S. troops should go home. Obama made his opposition to the U.S.-led invasion of Iraq five years ago a centerpiece of his campaign and was in Baghdad to assess security in Iraq, where violence has fallen to its lowest level since early 2004. When has Barack Obama visited Iraq? Which U.S. President’s have visited Iraq?

  6. Adding News Stories • Packages • Video/Audio • Related Video Segments • Closed Captioning Text • Ontology Refinement • Enter Objects of Interest • Growing Lexicons

  7. Data Frames and Relationship Sets “President Barack Obama visited Iraq”

  8. Extraction Ontology

  9. RDF Repository <rdf:RDFxmlns:sn="http://dithers.cs.byu.edu/owl/ontologies/SmartNews#"> <ann:CachedResourcerdf:ID="Video_1"> <ann:ResourceID>NewsStory1</ann:ResourceID> <ann:CachedURI>http://path.to.news.story/story1.wmv</ann:CachedURI> </ann:CachedResource> <rdf:Thingrdf:ID="Person_1"/> <rdf:Thingrdf:ID="Country_1"/> <rdf:Descriptionrdf:about="#Person_1"> <sn:Person-visited-Country rdf:resource="#Country_1"/> <sn:PersonValue>Barack Obama</sn:PersonValue> <ann:hasComponentrdf:resource="#PersonComponent_1"/> </rdf:Description> <rdf:Descriptionrdf:about="#Country_1"> <sn:CountryValue>Iraq</sn:CountryValue> <ann:hasComponentrdf:resource="#CountryComponent_1"/> </rdf:Description> </rdf:RDF>

  10. Querying • Seed with Story of Interest • Populated Search Form • SPARQL

  11. Evaluation • Query Story Repository • 10 “Seed” Stories • Quantitative • Expert Provide List of “Related Stories” • Compare Results • Qualitative • Present Results to Non-expert Users • Rate How well Story Relates to “Seed” Story

  12. Questions?

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