Semantic-based query techniques for source code NN Siddaramappa, R Sindhgatta, S Sarkar, S Thonse, K Pooloth US Patent 8,566,789, 2013 | 135 | 2013 |
Using an information retrieval system to retrieve source code samples R Sindhgatta Proceedings of the 28th international conference on Software engineering …, 2006 | 80 | 2006 |
Sentence level or token level features for automatic short answer grading?: Use both S Saha, TI Dhamecha, S Marvaniya, R Sindhgatta, B Sengupta Artificial Intelligence in Education: 19th International Conference, AIED …, 2018 | 75 | 2018 |
SOMA-ME: A platform for the model-driven design of SOA solutions LJ Zhang, N Zhou, YM Chee, A Jalaldeen, K Ponnalagu, RR Sindhgatta, ... IBM Systems Journal 47 (3), 397-413, 2008 | 75 | 2008 |
LINDA-BN: An interpretable probabilistic approach for demystifying black-box predictive models C Moreira, YL Chou, M Velmurugan, C Ouyang, R Sindhgatta, P Bruza Decision Support Systems 150, 113561, 2021 | 67 | 2021 |
SmartDispatch: enabling efficient ticket dispatch in an IT service environment S Agarwal, R Sindhgatta, B Sengupta Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 65 | 2012 |
Measuring the quality of service oriented design R Sindhgatta, B Sengupta, K Ponnalagu Service-Oriented Computing: 7th International Joint Conference, ICSOC …, 2009 | 59 | 2009 |
Augmenting classrooms with AI for personalized education R Kokku, S Sundararajan, P Dey, R Sindhgatta, S Nitta, B Sengupta 2018 IEEE international conference on acoustics, speech and signal …, 2018 | 51 | 2018 |
Exploring interpretable predictive models for business processes R Sindhgatta, C Moreira, C Ouyang, A Barros Business Process Management: 18th International Conference, BPM 2020 …, 2020 | 45 | 2020 |
Building interpretable models for business process prediction using shared and specialised attention mechanisms B Wickramanayake, Z He, C Ouyang, C Moreira, Y Xu, R Sindhgatta Knowledge-Based Systems 248, 108773, 2022 | 44 | 2022 |
Targeted example generation for compilation errors UZ Ahmed, R Sindhgatta, N Srivastava, A Karkare 2019 34th IEEE/ACM International Conference on Automated Software …, 2019 | 38 | 2019 |
Software system requirements specification framework and tool S Thonse, N Siddaramappa, R Sindhgatta, P Mahalingam, S Dhulipala, ... US Patent App. 11/084,730, 2006 | 38 | 2006 |
Memory-augmented neural networks for predictive process analytics A Khan, H Le, K Do, T Tran, A Ghose, H Dam, R Sindhgatta arXiv preprint arXiv:1802.00938 13, 2018 | 36 | 2018 |
Creating scoring rubric from representative student answers for improved short answer grading S Marvaniya, S Saha, TI Dhamecha, P Foltz, R Sindhgatta, B Sengupta Proceedings of the 27th ACM International Conference on Information and …, 2018 | 34 | 2018 |
Context-aware analysis of past process executions to aid resource allocation decisions R Sindhgatta, A Ghose, HK Dam Advanced Information Systems Engineering: 28th International Conference …, 2016 | 34 | 2016 |
Evaluating fidelity of explainable methods for predictive process analytics M Velmurugan, C Ouyang, C Moreira, R Sindhgatta International conference on advanced information systems engineering, 64-72, 2021 | 33 | 2021 |
Exploring interpretability for predictive process analytics R Sindhgatta, C Ouyang, C Moreira International Conference on Service-Oriented Computing, 439-447, 2020 | 33 | 2020 |
Software evolution in agile development: a case study R Sindhgatta, NC Narendra, B Sengupta Proceedings of the ACM international conference companion on Object oriented …, 2010 | 31 | 2010 |
The effect of machine learning explanations on user trust for automated diagnosis of COVID-19 K Goel, R Sindhgatta, S Kalra, R Goel, P Mutreja Computers in Biology and Medicine 146, 105587, 2022 | 30 | 2022 |
Characterizing the pedagogical benefits of adaptive feedback for compilation errors by novice programmers UZ Ahmed, N Srivastava, R Sindhgatta, A Karkare Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 30 | 2020 |