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Recommender system
Results: 1335

#	Item
601	1 A Customer Purchase Incidence Model Applied to Recommender Services Andreas Geyer-Schulz, Michael Hahsler, and Maximillian Jahn Abstract— In this contribution we transfer a customer purchase Add to Reading List Source URL: ai.stanford.edu Language: English - Date: 2001-07-19 13:35:49 Marketing Lysergic acid diethylamide Online shopping Consumer behaviour Collaborative filtering Normal distribution Logarithm Human behavior Information science Statistics Recommender system
602	Hebbian Algorithms for a Digital Library Recommendation System Francis Heylighen CLEA, Free University of Brussels http://pcp.vub.ac.be/HEYL.html Johan Bollen Add to Reading List Source URL: pespmc1.vub.ac.be Language: English - Date: 2014-05-02 12:27:42 Information Natural language processing Data mining Semantics Recommender system Collaborative filtering Subject Spreading activation Relevance Information science Science Information retrieval
603	Online Selection of Mediated and Domain-Specific Predictions for Improved Recommender Systems Stephanie Rosenthal, Manuela Veloso, Anind Dey School of Computer Science Carnegie Mellon University {srosenth,veloso,anind}@c Add to Reading List Source URL: webscope.sandbox.yahoo.com Language: English - Date: 2014-11-13 19:03:20 Review websites Recommender system Review
604	INDUSTRY TRENDS Recommendation Technology: Will it Boost E-Commerce? Add to Reading List Source URL: www.leavcom.com Language: English - Date: 2013-04-12 14:46:20 Electronic commerce Human–computer interaction Business Recommender system Web services Collaborative filtering Online shopping Personalization GroupLens Research Information science Information retrieval Marketing
605	Collaborative Filtering and the Missing at Random Assumption Benjamin M. Marlin Richard S. Zemel Yahoo! Research and Department of Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2009-06-29 08:36:44 Cluster analysis Collaborative filtering Social information processing Mixture model Expectation–maximization algorithm Recommender system Conjugate prior Statistical model Maximum likelihood Statistics Estimation theory Statistical theory
606	Eigentaste 5.0: Constant-Time Adaptability in a Recommender System Using Item Clustering Tavi Nathanson Ephrat Bitton Add to Reading List Source URL: www.ieor.berkeley.edu Language: English - Date: 2007-08-31 03:30:28 Information systems Science Collaboration Social information processing Information retrieval Collaborative filtering Recommender system Cold start Cluster analysis Statistics Information science Collective intelligence
607	Information Retrieval, 4, 133–151, 2001 c 2001 Kluwer Academic Publishers. Manufactured in The Netherlands. Eigentaste: A Constant Time Collaborative Filtering Algorithm Add to Reading List Source URL: www.ieor.berkeley.edu Language: English - Date: 2006-03-09 10:49:42 Information retrieval Multivariate statistics Collective intelligence Collaboration Singular value decomposition Collaborative filtering Recommender system GroupLens Research Principal component analysis Algebra Linear algebra Statistics
608	Solution Brief: Personalized Onsite Search Personalized Product and Content Search Baynote’s behavior based approach unifies search and recommendations to provide improved navigation and personalized product and Add to Reading List Source URL: www.demandware.com Language: English - Date: 2015-03-03 17:58:05 Marketing Web services Baynote Search engine optimization Search engine marketing Recommender system Personalization Online shopping Internet Internet marketing Computing
609	[removed]Science2.0-Presentation_v4.key Add to Reading List Source URL: www.science20-conference.eu Language: English - Date: 2015-04-01 16:17:45 Social media Text messaging Twitter Websites Web portal Recommender system Integrated Digital Enhanced Network Brand page Computing World Wide Web Technology Real-time web
610	Problem Description Study how to adaptively aggregate recommender systems on a per-user and per-item basis when combining results from complementing prediction methods. Create a flexible algorithm that combines multiple Add to Reading List Source URL: www.bjorkoy.com Language: English - Date: 2014-07-08 05:02:10 Human–computer interaction Personalization Science Collective intelligence Information science Information retrieval Recommender system

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