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Social information processing / Collective intelligence / Information retrieval / Metadata / Tag / GroupLens Research / Flickr / Polyhistidine-tag / Models of collaborative tagging / Information / Web 2.0 / World Wide Web


More Efficient Tagging Systems with Tag Seeding 1 Vikas Kumar1 , Daniel Kluver1 , Loren Terveen1 , John Riedl1 GroupLens Research - University of Minnesota, Twin Cities, USA vikas,kluver,[removed]
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Document Date: 2014-07-23 18:52:33


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City

Graz / /

Company

Related Work Collaborative Tagging Systems / D. Frankowski / Efficient Tagging Systems / /

Country

Austria / /

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Facility

University of Minnesota / /

IndustryTerm

applications i.e. current applications / movie recommendation site / controlled study to elicit more applications / similar systems / large then current applications / distinct user tag applications / higher search / enough tag applications / tag search results / online information / social tagging systems / movie search pages / their existing applications / tag search / collaborative tagging systems / tag applications / ONLINE INFORMATION-INTERNATIONAL MEETING / search efficiency / /

Movie

Supply and Demand / /

Organization

National Science Foundation / National Academy of Sciences / University of Minnesota / /

Person

Baseline / C. Cattuto / V / Seuss / Ting-Yu Wang / Clay Shirky / /

Position

Harper / and J. Riedl / detective / /

ProgrammingLanguage

C / /

PublishedMedium

Proceedings of the National Academy of Sciences / Communications of the ACM / /

TVShow

The Cat in the Hat / /

Technology

Opportunity Gap algorithm / Baseline algorithm / knowledge management / Hybrid algorithm / Baseline algorithms / Potential algorithms / user Algorithm / RQ2 /

SocialTag