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Recommender system
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#	Item
941	Who Can Use What? Proposals for the Development of a Recommender System for Selecting the Most Appropriate Text Input Method for a Given User Based on the User’s Physical Abilities. By Carl Sigmond Department of Comput Add to Reading List Source URL: www.carlsigmond.com Language: English - Date: 2013-10-25 02:08:58 Computer hardware Computer keyboards Input/output Virtual reality User interface Virtual keyboard Pen computing Input method Apple Keyboard Humanâ€“computer interaction Computing User interface techniques
942	Recommend a Movie, Win a Million Bucks Can a computer learn to choose movies you’re sure to like? Artificial intelligence took on this real-world problem in the Netflix contest. A Caltech alum recounts his Add to Reading List Source URL: eands.caltech.edu Language: English - Date: 2011-10-07 19:51:45 Netflix Business Reed Hastings Opera Solutions Recommender system Machine learning Ensemble learning Root-mean-square deviation Statistics Crowdsourcing Netflix Prize
943	Start-Up Chile Application Question Note: this document is for your preparation purposes only. You must submit your application using the online form. No printed applications will be accepted. Startup Information Add to Reading List Source URL: img.startupchile.org Language: English - Date: 2014-06-04 14:02:31 Recommender system Export Chile Passport Minimum viable product International relations Science Business Chilean passport YouNoodle
944	WRITING RECOMMENDATION LETTERS Getting Started: Make sure you include: • Applicant’s full name, field of study and country of application as well as recommender’s contacts, full name, title and signature. Add to Reading List Source URL: www.fulbright.cz Language: English - Date: 2014-02-06 18:56:00 Recommendation letter Recommender system Professor Letter Employment Recruitment Education Academia Knowledge
945	Center/Classroom: ________________________________ Teachers:_____________________________ Date/Time ___________ Subscales and Items on the FCCERS-R Consultation and Observation SPACE AND FURNISHING Add to Reading List Source URL: www.qualistar.org Language: English - Date: 2011-10-13 15:33:25
946	Enhancement of the Neutrality in Recommendation Toshihiro Kamishima, Shotaro Akaho, and Hideki Asoh National Institute of Advanced Industrial Science and Technology (AIST) AIST Tsukuba Central 2, Umezono 1-1-1, Add to Reading List Source URL: recex.ist.tugraz.at Language: English - Date: 2012-09-08 17:28:10 Information Science Recommender systems Social information processing Collective intelligence GroupLens Research Collaborative filtering Filter bubble Information filtering system Information science Human–computer interaction Information retrieval
947	Center/Classroom: ________________________________ Teachers:_____________________________ Date/Time ___________ Subscales and Items on the ECERS-R Consultation and Observation SPACE AND FURNISHING Add to Reading List Source URL: www.qualistar.org Language: English - Date: 2011-10-13 15:32:34
948	Microsoft Word - RecSys_RUE2012_v6(CameraReady) Add to Reading List Source URL: ir.ii.uam.es Language: English - Date: 2012-09-25 10:47:46 Information retrieval Collaboration Collective intelligence Social information processing Recommender system Collaborative filtering GroupLens Research Netflix Prize Netflix Algebra Mathematics Statistics
949	Girl Empower: The NFTE Summer BizCamp Experience® Summer 2013 Add to Reading List Source URL: www.nfte.com Language: English - Date: 2013-05-07 16:38:08 Email Question Business Computing Social psychology Entrepreneurship Network For Teaching Entrepreneurship Recommender system
950	Center/Classroom: ________________________________ Teachers:_____________________________ Date/Time ___________ Subscales and Items on the ITERS-R Consultation and Observation SPACE AND FURNISHING Add to Reading List Source URL: www.qualistar.org Language: English - Date: 2011-10-13 15:33:00

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