Explainable Matrix Factorization for Collaborative Filtering Behnoush Abdollahi Olfa Nasraoui Knowledge Discovery & Web Mining Lab

Source URL: gdac.uqam.ca

• Recommender systems
• Information science
• Collective intelligence
• Information retrieval
• Humancomputer interaction
• Collaboration
• Information systems
• Matrix factorization
• Collaborative filtering
• GroupLens Research
• Non-negative matrix factorization
• QJ

J. Hlaváˇcová (Ed.): ITAT 2017 Proceedings, p. 2 c 2017 A. Lige¸za CEUR Workshop Proceedings Vol. 1885, ISSN, Rules, Causality and Constraints. Model-Based Reasoning and Structural Knowledge Discovery

Source URL: ceur-ws.org

2012 Ninth International Joint Conference on Computer Science and Software Engineering (JCSSE) Knowledge Discovery in Web Traffic Log: A Case Study of Facebook Usage in Kasetsart University Chakkrit Tantithamthavorn, A

Source URL: chakkrit.com

Bioinformatics Group Institute for Knowledge Discovery Master Thesis Dr. techn. Jürgen Hartler

Source URL: genome.tugraz.at

Towards the Discovery of Implicit Metadata in Commercial Web Pages Vojtˇech Sv´atek, Martin Kavalec and Jiˇr´ı Klemperer Department of Information and Knowledge Engineering, University of Economics, Prague, W. Churc

Source URL: iswc2002.semanticweb.org

Stages of Knowledge Discovery in Web Sites Matthew Smith and Christophe Giraud-Carrier Brigham Young University, Department of Computer Science, Provo, UT 84602, USA Abstract E-commerce greatly facilitates and enhances t

Source URL: m.smithworx.com

Discovery of potential collaboration networks from open knowledge sources Nelson Piedra1, Janneth Chicaiza1, Jorge Lopez-Vargas1 and Edmundo Tovar2 1 Universidad Técnica Particular de Loja, Loja, Ecuador

Source URL: 2017.kesw.ru

2nd International Biocuration Meeting San Jose, California October, 2007 Curating the Comparative Toxicogenomics Database: a knowledge and discovery environment for chemical-gene-disease associations Allan Peter

Source URL: ctd.mdibl.org

ANGELA WILCZYNSKI/WIZZLE.SIMPLENET.COM/FRACTALS/FRACTALINTRO.HTM Knowledge Discovery in Deep Blue A vast database of human experience can be

Source URL: www.top-5000.nl

Knowledge Discovery in Chess Databases: A Research Proposal Johannes Furnkranz ¨ Austrian Research Institute for Artificial Intelligence Schottengasse 3, A-1010 Wien, Austria E-mail:

Source URL: www.top-5000.nl