| A Belief-Driven Method for Discovering Unexpected Patterns. B Padmanabhan, A Tuzhilin KDD 98, 94-100, 1998 | 394 | 1998 |
| Scene: a scalable two-stage personalized news recommendation system L Li, D Wang, T Li, D Knox, B Padmanabhan Proceedings of the 34th international ACM SIGIR conference on Research and …, 2011 | 332 | 2011 |
| Unexpectedness as a measure of interestingness in knowledge discovery B Padmanabhan, A Tuzhilin Decision Support Systems 27 (3), 303-318, 1999 | 297 | 1999 |
| Do social features help in video-centric online learning platforms? A social presence perspective SA Andel, T de Vreede, PE Spector, B Padmanabhan, VK Singh, ... Computers in Human Behavior 113, 106505, 2020 | 256 | 2020 |
| AI hallucinations: a misnomer worth clarifying N Maleki, B Padmanabhan, K Dutta 2024 IEEE conference on artificial intelligence (CAI), 133-138, 2024 | 238 | 2024 |
| Small is beautiful: discovering the minimal set of unexpected patterns B Padmanabhan, A Tuzhilin Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000 | 200 | 2000 |
| Building digital resilience against major shocks W Boh, P Constantinides, B Padmanabhan, S Viswanathan MIS quarterly 47 (1), 343-360, 2023 | 192 | 2023 |
| Editorial for the special section on humans, algorithms, and augmented intelligence: The future of work, organizations, and society H Jain, B Padmanabhan, P Pavlou, TS Raghu Information Systems Research 32 (3), 675-687, 2021 | 169 | 2021 |
| On the use of optimization for data mining: Theoretical interactions and eCRM opportunities B Padmanabhan, A Tuzhilin Management Science 49 (10), 1327-1343, 2003 | 158 | 2003 |
| Editor’s comments: Machine learning in information systems research B Padmanabhan, X Fang, N Sahoo, A Burton-Jones MIS quarterly 46 (1), iii-xix, 2022 | 127 | 2022 |
| Personalization from incomplete data: What you don't know can hurt B Padmanabhan, Z Zheng, SO Kimbrough Proceedings of the seventh ACM SIGKDD international conference on Knowledge …, 2001 | 117 | 2001 |
| Ew-tune: A framework for privately fine-tuning large language models with differential privacy R Behnia, MR Ebrahimi, J Pacheco, B Padmanabhan 2022 IEEE International Conference on Data Mining Workshops (ICDMW), 560-566, 2022 | 111 | 2022 |
| An empirical analysis of the value of complete information for eCRM models B Padmanabhan, Z Zheng, SO Kimbrough Mis Quarterly, 247-267, 2006 | 110 | 2006 |
| From business intelligence to competitive intelligence: Inferring competitive measures using augmented site-centric data Z Zheng, P Fader, B Padmanabhan Information Systems Research 23 (3-part-1), 698-720, 2012 | 103 | 2012 |
| On active learning for data acquisition Z Zheng, B Padmanabhan 2002 IEEE International Conference on Data Mining, 2002. Proceedings., 562-569, 2002 | 102 | 2002 |
| On the discovery of significant statistical quantitative rules H Zhang, B Padmanabhan, A Tuzhilin Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004 | 99 | 2004 |
| Selectively acquiring customer information: A new data acquisition problem and an active learning-based solution Z Zheng, B Padmanabhan Management Science 52 (5), 697-712, 2006 | 90 | 2006 |
| Deep Learning for Information Systems Research S Samtani, H Zhu, B Padmanabhan, Y Chai, H Chen https://arxiv.org/abs/2010.05774, 2020 | 84 | 2020 |
| Pattern Discovery in Temporal Databases: A Temporal Logic Approach. B Padmanabhan, A Tuzhilin KDD, 351-354, 1996 | 84 | 1996 |
| Taming complexity in search matching: Two-sided recommender systems on digital platforms O Malgonde, H Zhang, B Padmanabhan, M Limayem Mis Quarterly 44 (1), 49-84, 2020 | 83 | 2020 |
