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A Scalable Approach to Learn Semantic Models of Structured Sources Mohsen Taheriyan, Craig A. Knoblock, Pedro Szekely, Jos´e Luis Ambite Information Sciences Institute and Computer Science Department University of South
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Document Date: 2014-07-17 21:22:06


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City

FOAF / /

Company

Air Force Research Laboratory / Intel / /

Country

United States / /

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Event

Reorganization / /

Facility

Dallas Museum of Art / The Metropolitan Museum of Art / Building A Graph / Dallas Museum / Jos´e Luis Ambite Information Sciences Institute / Smithsonian American Art Museum / Indianapolis Museum of Art / Computer Science Department University of Southern California / Automatically building / /

IndustryTerm

approximation algorithm / machine learning algorithm / Online Information Sources / Web Tables Using Entities / Web research / tree algorithm / search space / Web APIs / search algorithm / learning algorithm / /

OperatingSystem

Mac OS X / /

Organization

National Science Foundation / University of Southern California / U.S. Government / Jos´e Luis Ambite Information Sciences Institute / Smithsonian / /

Person

Luis Ambite / Craig A. Knoblock / Carman / Morgan Kauffman / /

Position

aac /

Product

M0 / C-7058 / /

ProgrammingLanguage

XML / /

ProvinceOrState

Oregon / /

PublishedMedium

Machine Learning / Journal of Artificial Intelligence Research / /

RadioStation

Core / /

Region

Southern California / /

Technology

learning algorithm / mapping algorithm / JSON / search algorithm / approximation algorithm / machine learning algorithm / Steiner tree algorithm / machine learning / domain ontology O. The algorithm / RDF / operating system / /

URL

www.europeana / www.dma.org / www.metmuseum.org / www.w3.org/2008/05/skos# / www.americanartcollaborative.org / www.openarchives.org/ore/terms / www.imamuseum.org / /

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