| Industrial applications of answer set programming A Falkner, G Friedrich, K Schekotihin, R Taupe, EC Teppan KI-Künstliche Intelligenz 32 (2), 165-176, 2018 | 125 | 2018 |
| Consumer decision making in knowledge-based recommendation M Mandl, A Felfernig, E Teppan, M Schubert Journal of intelligent information systems 37, 1-22, 2011 | 123 | 2011 |
| A short survey of recommendation technologies in travel and tourism A Felfernig, S Gordea, D Jannach, E Teppan, M Zanker OEGAI journal 25 (7), 17-22, 2007 | 107 | 2007 |
| Plausible Repairs for Inconsistent Requirements. A Felfernig, G Friedrich, M Schubert, M Mandl, M Mairitsch, E Teppan IJCAI 9, 791-796, 2009 | 102 | 2009 |
| Persuasive recommendation: serial position effects in knowledge-based recommender systems A Felfernig, G Friedrich, B Gula, M Hitz, T Kruggel, G Leitner, R Melcher, ... Persuasive Technology: Second International Conference on Persuasive …, 2007 | 95 | 2007 |
| Knowledge-based recommender technologies for marketing and sales A Felfernig, E Teppan, B Gula International journal of pattern recognition and artificial intelligence 21 …, 2007 | 82 | 2007 |
| Persuasion in knowledge-based recommendation A Felfernig, B Gula, G Leitner, M Maier, R Melcher, E Teppan Persuasive Technology: Third International Conference, PERSUASIVE 2008, Oulu …, 2008 | 64 | 2008 |
| Industrial-size job shop scheduling with constraint programming G Da Col, EC Teppan Operations Research Perspectives 9, 100249, 2022 | 47 | 2022 |
| Industrial size job shop scheduling tackled by present day CP solvers G Da Col, EC Teppan Principles and Practice of Constraint Programming: 25th International …, 2019 | 47 | 2019 |
| Decision biases in recommender systems EC Teppan, M Zanker Journal of Internet Commerce 14 (2), 255-275, 2015 | 47 | 2015 |
| Automated debugging of recommender user interface descriptions A Felfernig, G Friedrich, K Isak, K Shchekotykhin, E Teppan, D Jannach Applied Intelligence 31, 1-14, 2009 | 33 | 2009 |
| Utility-based repair of inconsistent requirements A Felfernig, M Mairitsch, M Mandl, M Schubert, E Teppan Next-Generation Applied Intelligence: 22nd International Conference on …, 2009 | 30 | 2009 |
| Intelligent debugging and repair of utility constraint sets in knowledge-based recommender applications A Felfernig, E Teppan, G Friedrich, K Isak Proceedings of the 13th international conference on Intelligent user …, 2008 | 30 | 2008 |
| Google vs IBM: A constraint solving challenge on the job-shop scheduling problem G Da Col, E Teppan arXiv preprint arXiv:1909.08247, 2019 | 29 | 2019 |
| Quickpup: A heuristic backtracking algorithm for the partner units configuration problem E Teppan, G Friedrich, A Falkner Proceedings of the AAAI Conference on Artificial Intelligence 26 (2), 2329-2334, 2012 | 29 | 2012 |
| Minimization of decoy effects in recommender result sets EC Teppan, A Felfernig Web Intelligence and Agent Systems: An International Journal 10 (4), 385-395, 2012 | 29 | 2012 |
| Asymmetric dominance-and compromise effects in the financial services domain EC Teppan, A Felfernig 2009 IEEE conference on commerce and enterprise computing, 57-64, 2009 | 28* | 2009 |
| A dominance model for the calculation of decoy products in recommendation environments A Felfernig, B Gula, G Leitner, M Maier, R Melcher, S Schippel, E Teppan AISB 2008 symposium on persuasive technology, 43-50, 2008 | 25 | 2008 |
| Minimization of product utility estimation errors in recommender result set evaluations EC Teppan, A Felfernig Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web …, 2009 | 20 | 2009 |
| Calculating decoy items in utility-based recommendation EC Teppan, A Felfernig International Conference on Industrial, Engineering and Other Applications …, 2009 | 19 | 2009 |
Alexander FelfernigProfessor of Computer Science, Graz University of Technology, AustriaPatvirtintas el. paštas tugraz.at