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Linear algebra / Human–computer interaction / Recommender systems / Collective intelligence / Collaborative filtering / Singular value decomposition / GroupLens Research / Latent semantic indexing / Orthogonal matrix / Algebra / Information science / Information retrieval


Application of Dimensionality Reduction in Recommender System -- A Case Study Badrul M. Sarwar, George Karypis, Joseph A. Konstan, John T. Riedl GroupLens Research Group / Army HPC Research Center
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Document Date: 2013-10-21 15:54:18


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File Size: 145,33 KB

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Company

Joseph A. Konstan / Digital Equipment Corporation / CDnow.com / Pearson / John T. Riedl GroupLens Research Group / Amazon / /

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Event

Product Recall / Product Issues / /

Facility

Engineering University of Minnesota Minneapolis / /

IndustryTerm

recommender algorithm / agent solution / Recommendation algorithms / matrix product / inner product / collaborative filtering recommender systems / matrix factorization algorithm / recommender system algorithms / typical web-based recommender system / model to recommend products / Web server software displays / dot product / particular product / recommender systems / Web access patterns / e-commerce data / data analysis software / web systems / neighbor algorithms / Web interface / online performance / recommender system technology / e-commerce sites / matrix products / neural network / collaborative filtering algorithms / large e-commerce / recycled memo pad products / recycled letter pad products / ratings-based automated collaborative filtering systems / pseudonymous collaborative filtering solution / e-commerce dataset / particular products / prediction generation algorithm / Web server software / e - commerce / prediction algorithms / online component / nearest neighbor algorithm / model-based technology / ecommerce data / prediction algorithm / outbound telephone campaigns / recommender system technologies / recycled office products / web-based research recommender system / select high-quality products / retail store inventory / nearest neighbor algorithms / /

Organization

Computer Science and Engineering University of Minnesota Minneapolis / Army HPC Research Center Department of Computer Science / /

Person

Sue / Paul / Mike / George Karypis / /

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Position

analyst / /

Product

MovieLens / community namely / MovieLens recommender system / F1 / /

ProgrammingLanguage

EC / R / HTML / ML / /

Technology

Recommendation algorithms / recommender system technologies / SVD-based recommender algorithm / SVD-based prediction algorithm / nearest neighbor algorithm / collaborative filtering algorithms / classical CF algorithm / SVD algorithms / how one model-based technology / prediction algorithms / correlation-based CF algorithm / correlation-based algorithm / one technology / recommender system technology / underlying matrix factorization algorithm / Nearest neighbor algorithms / neural network / prediction generation algorithm / DHTML / alternative recommender system algorithms / sparse SVD algorithms / Web server / SVD-based prediction generation algorithm / /

URL

www.cdnow.com / www.movielens.umn.edu / www.amazon.com / /

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