| Identifying helpful online reviews: A product designer’s perspective Y Liu, J Jin, P Ji, JA Harding, RYK Fung Computer-Aided Design 45 (2), 180-194, 2013 | 224 | 2013 |
| Understanding big consumer opinion data for market-driven product design J Jin, Y Liu, P Ji, H Liu International Journal of Production Research 54 (10), 3019-3041, 2016 | 203 | 2016 |
| Identifying comparative customer requirements from product online reviews for competitor analysis J Jin, P Ji, R Gu Engineering Applications of Artificial Intelligence 49, 61-73, 2016 | 198 | 2016 |
| Quantification and integration of Kano’s model into QFD for optimising product design P Ji, J Jin, T Wang, Y Chen International Journal of Production Research 52 (21), 6335-6348, 2014 | 132 | 2014 |
| Review on recent advances in information mining from big consumer opinion data for product design J Jin, Y Liu, P Ji, CK Kwong Journal of Computing and Information Science in Engineering 19 (1), 010801, 2019 | 99 | 2019 |
| Translating online customer opinions into engineering characteristics in QFD: A probabilistic language analysis approach J Jin, P Ji, Y Liu, SCJ Lim Engineering Applications of Artificial Intelligence 41, 115-127, 2015 | 93 | 2015 |
| A biclustering-based method for market segmentation using customer pain points B Wang, Y Miao, H Zhao, J Jin, Y Chen Engineering Applications of Artificial Intelligence 47, 101-109, 2016 | 74 | 2016 |
| Mining online reviews with a Kansei-integrated Kano model for innovative product design J Jin, D Jia, K Chen International Journal of Production Research 60 (22), 6708-6727, 2022 | 61 | 2022 |
| What makes consumers unsatisfied with your products: Review analysis at a fine-grained level J Jin, P Ji, CK Kwong Engineering Applications of Artificial Intelligence 47, 38-48, 2016 | 58 | 2016 |
| Prioritising engineering characteristics based on customer online reviews for quality function deployment J Jin, P Ji, Y Liu Journal of Engineering Design 25 (7-9), 303-324, 2014 | 51 | 2014 |
| Single machine scheduling with truncated job-dependent learning effect XR Wang, JB Wang, J Jin, P Ji Optimization Letters 8, 669-677, 2014 | 37 | 2014 |
| How to interpret the helpfulness of online product reviews: bridging the needs between customers and designers J Jin, Y Liu Proceedings of the 2nd international workshop on Search and mining user …, 2010 | 37 | 2010 |
| Integrating the trend of research interest for reviewer assignment J Jin, Q Geng, Q Zhao, L Zhang Proceedings of the 26th international conference on World Wide Web Companion …, 2017 | 32 | 2017 |
| An integer linear programming model of reviewer assignment with research interest considerations J Jin, B Niu, P Ji, Q Geng Annals of Operations Research 291, 409-433, 2020 | 25 | 2020 |
| Author–Subject–Topic model for reviewer recommendation J Jin, Q Geng, H Mou, C Chen Journal of Information Science 45 (4), 554-570, 2019 | 24 | 2019 |
| Automated overheated region object detection of photovoltaic module with thermography image Y Su, F Tao, J Jin, C Zhang IEEE Journal of Photovoltaics 11 (2), 535-544, 2021 | 22 | 2021 |
| Cross-domain ontology construction and alignment from online customer product reviews Q Geng, S Deng, D Jia, J Jin Information Sciences 531, 47-67, 2020 | 22 | 2020 |
| Resource-dependent scheduling with deteriorating jobs and learning effects on unrelated parallel machine YY Lu, J Jin, P Ji, JB Wang Neural Computing and Applications 27, 1993-2000, 2016 | 21 | 2016 |
| Integrating topic, sentiment, and syntax for modeling online reviews: a topic model approach M Tang, J Jin, Y Liu, C Li, W Zhang Journal of Computing and Information Science in Engineering 19 (1), 011001, 2019 | 17 | 2019 |
| Big consumer opinion data understanding for Kano categorization in new product development K Chen, J Jin, J Luo Journal of Ambient Intelligence and Humanized Computing, 1-20, 2022 | 16 | 2022 |
Ping JiKhalifa University of Science and TechnologyGeverifieerd e-mailadres voor ku.ac.ae
