| On the Benefits and Pitfalls of Analogies for Innovative Design: Ideation Performance Based on Analogical Distance, Commonness, and Modality of Examples J Chan, K Fu, C Schunn, J Cagan, K Wood, K Kotovsky Journal of Mechanical Design 133, 081004, 2011 | 379 | 2011 |
| The Meaning of “Near” and “Far”: The Impact of Structuring Design Databases and the Effect of Distance of Analogy on Design Output K Fu, J Chan, J Cagan, K Kotovsky, C Schunn, K Wood ASME 2012 International Design Engineering Technical Conferences and …, 2012 | 368 | 2012 |
| The meaning of “near” and “far”: the impact of structuring design databases and the effect of distance of analogy on design output K Fu, J Chan, J Cagan, K Kotovsky, C Schunn, K Wood Journal of Mechanical Design 135 (2), 021007, 2013 | 346 | 2013 |
| Do The Best Design Ideas (Really) Come From Conceptually Distant Sources Of Inspiration? J Chan, SP Dow, CD Schunn Design Studies, 2014 | 204* | 2014 |
| The impact of analogies on creative concept generation: lessons from an in vivo study in engineering design J Chan, C Schunn Cognitive science 39 (1), 126-155, 2015 | 135 | 2015 |
| Providing Timely Examples Improves the Quantity and Quality of Generated Ideas P Siangliulue, J Chan, KZ Gajos, SP Dow Proceedings of the ACM Conference on Creativity and Cognition, 2015 | 127 | 2015 |
| IdeaHound: Improving Large-scale Collaborative Ideation with Crowd-Powered Real-time Semantic Modeling P Siangliulue, J Chan, SP Dow, KZ Gajos Proceedings of the 29th Annual Symposium on User Interface Software and …, 2016 | 114 | 2016 |
| Improving Crowd Innovation with Expert Facilitation J Chan, S Dang, SP Dow Proceedings of the ACM Conference on Computer-Supported Cooperative Work, 2016 | 108 | 2016 |
| Scaling up analogical innovation with crowds and AI A Kittur, L Yu, T Hope, J Chan, H Lifshitz-Assaf, K Gilon, F Ng, RE Kraut, ... Proceedings of the National Academy of Sciences 116 (6), 1870-1877, 2019 | 106 | 2019 |
| Scaling up analogical innovation with crowds and AI A Kittur, L Yu, T Hope, J Chan, H Lifshitz-Assaf, K Gilon, F Ng, RE Kraut, ... Proceedings of the National Academy of Sciences 116 (6), 1870-1877, 2019 | 106 | 2019 |
| Accelerating Innovation Through Analogy Mining T Hope, J Chan, A Kittur, D Shahaf Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 99 | 2017 |
| Solvent: A mixed initiative system for finding analogies between research papers J Chan, JC Chang, T Hope, D Shahaf, A Kittur Proceedings of the ACM on Human-Computer Interaction 2 (CSCW), 1-21, 2018 | 96 | 2018 |
| Analogy as a strategy for supporting complex problem solving under uncertainty J Chan, SBF Paletz, CD Schunn Memory & cognition 40, 1352-1365, 2012 | 94 | 2012 |
| The importance of iteration in creative conceptual combination J Chan, CD Schunn Cognition 145, 104-115, 2015 | 78 | 2015 |
| Semantically Far Inspirations Considered Harmful?: Accounting for Cognitive States in Collaborative Ideation J Chan, P Siangliulue, D Qori McDonald, R Liu, R Moradinezhad, S Aman, ... Proceedings of the 2017 ACM SIGCHI Conference on Creativity and Cognition …, 2017 | 71 | 2017 |
| The dynamics of micro-conflicts and uncertainty in successful and unsuccessful design teams SBF Paletz, J Chan, CD Schunn Design Studies 50, 39-69, 2017 | 69 | 2017 |
| Crowdboard: Augmenting In-Person Idea Generation with Real-Time Crowds S Andolina, H Schneider, J Chan, K Klouche, G Jacucci, S Dow Proceedings of the 2017 ACM SIGCHI Conference on Creativity and Cognition …, 2017 | 62 | 2017 |
| Understanding Older Adults' Participation in Design Workshops A Pradhan, B Jelen, KA Siek, J Chan, A Lazar Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems …, 2020 | 60 | 2020 |
| Comparing Different Sensemaking Approaches for Large-Scale Ideation J Chan, S Dang, SP Dow Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems …, 2016 | 57 | 2016 |
| Learning to Recommend Visualizations from Data X Qian, RA Rossi, F Du, S Kim, E Koh, S Malik, TY Lee, J Chan Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 50 | 2021 |
Christian SchunnProfessor of Psychology, University of Pittsburghpitt.edu의 이메일 확인됨