![Crowdsourcing / Netflix Prize / Science / Collaboration / K-nearest neighbor algorithm / Recommender system / Noise reduction / Collaborative filtering / Rating scale / Information science / Image processing / Collective intelligence Crowdsourcing / Netflix Prize / Science / Collaboration / K-nearest neighbor algorithm / Recommender system / Noise reduction / Collaborative filtering / Rating scale / Information science / Image processing / Collective intelligence](https://www.pdfsearch.io/img/bcb4d700043199ebdecf28f7b1dce55b.jpg)
| Document Date: 2014-01-06 00:18:35 Open Document File Size: 135,64 KBShare Result on Facebook
City Datasets User / Denoising User / / Company Netflix / INTRODUCTION AND MOTIVATION Recommender Systems / Recommender Systems / Telefonica / / Currency USD / Rs / / / Event M&A / / IndustryTerm baseline algorithm / recommendation algorithm / recommendation algorithms / representative algorithms / explained datadependent denoising algorithm / Web #Ti T1 / user-dependent denoising algorithm / proposed denoising algorithm / re-rating algorithm / particular algorithm / / Person Nuria Oliver / Nava Tintarev / Xavier Amatriain Josep / / Position R. Rafter / rt / representative / / ProvinceOrState New Jersey / / PublishedMedium The Public Opinion Quarterly / / Technology previous one-source re-rating algorithm / recommendation algorithms / recommendation algorithm / three algorithms / baseline algorithm / particular algorithm / proposed algorithm / proposed denoising algorithm / user-dependent denoising algorithm / CF algorithms / The algorithm / previously explained datadependent denoising algorithm / denoising algorithm / same algorithm / 2.1 Algorithm / studied algorithms / five algorithms / two representative algorithms / virtual community / /
SocialTag |