| SeeDB: efficient data-driven visualization recommendations to support visual analytics M Vartak, S Rahman, S Madden, A Parameswaran, N Polyzotis Proceedings of the VLDB Endowment 8 (13), 2182-2193, 2015 | 312 | 2015 |
| CrowdScreen: Algorithms for Filtering Data with Humans A Parameswaran, H Garcia-Molina, H Park, N Polyzotis, A Ramesh, ... Stanford InfoLab, 2011 | 289 | 2011 |
| Datahub: Collaborative data science & dataset version management at scale A Bhardwaj, S Bhattacherjee, A Chavan, A Deshpande, AJ Elmore, ... arXiv preprint arXiv:1409.0798, 2014 | 242 | 2014 |
| So who won? Dynamic max discovery with the crowd S Guo, A Parameswaran, H Garcia-Molina Proceedings of the 2012 ACM SIGMOD international conference on management of …, 2012 | 227 | 2012 |
| Recommendation systems with complex constraints: A course recommendation perspective A Parameswaran, P Venetis, H Garcia-Molina ACM Transactions on Information Systems (TOIS) 29 (4), 20, 2011 | 205 | 2011 |
| Recommendation systems with complex constraints: A courserank perspective A Parameswaran, P Venetis, H Garcia-Molina Transactions on Information Systems (TOIS)--To Appear, 2011 | 205* | 2011 |
| Human-assisted graph search: it's okay to ask questions A Parameswaran, AD Sarma, H Garcia-Molina, N Polyzotis, J Widom Proceedings of the VLDB Endowment 4 (5), 267-278, 2011 | 186 | 2011 |
| Effortless data exploration with zenvisage: an expressive and interactive visual analytics system T Siddiqui, A Kim, J Lee, K Karahalios, A Parameswaran arXiv preprint arXiv:1604.03583, 2016 | 174 | 2016 |
| Challenges in data crowdsourcing H Garcia-Molina, M Joglekar, A Marcus, A Parameswaran, V Verroios IEEE Transactions on Knowledge and Data Engineering 28 (4), 901-911, 2016 | 170 | 2016 |
| Towards visualization recommendation systems M Vartak, S Huang, T Siddiqui, S Madden, A Parameswaran Acm Sigmod Record 45 (4), 34-39, 2017 | 159 | 2017 |
| Answering queries using humans, algorithms and databases A Parameswaran, N Polyzotis Stanford InfoLab, 2011 | 148 | 2011 |
| Accelerating human-in-the-loop machine learning: Challenges and opportunities D Xin, L Ma, J Liu, S Macke, S Song, A Parameswaran Proceedings of the second workshop on data management for end-to-end machine …, 2018 | 146 | 2018 |
| Deco: Declarative Crowdsourcing A Parameswaran, H Park, H Garcia-Molina, N Polyzotis, J Widom Stanford InfoLab, 2012 | 146 | 2012 |
| Fuzzy Joins Using MapReduce FN Afrati, AD Sarma, D Menestrina, A Parameswaran, JD Ullman Stanford InfoLab, 2012 | 139 | 2012 |
| Active Sampling for Entity Matching K Bellare, S Iyengar, A Parameswaran, V Rastogi Stanford InfoLab, 2012 | 133 | 2012 |
| Evaluating the crowd with confidence M Joglekar, H Garcia-Molina, A Parameswaran Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013 | 132 | 2013 |
| Rapid sampling for visualizations with ordering guarantees A Kim, E Blais, A Parameswaran, P Indyk, S Madden, R Rubinfeld Proceedings of the vldb endowment international conference on very large …, 2015 | 123 | 2015 |
| Interactive data exploration with smart drill-down M Joglekar, H Garcia-Molina, A Parameswaran IEEE Transactions on Knowledge and Data Engineering 31 (1), 46-60, 2017 | 117* | 2017 |
| Towards the web of concepts: Extracting concepts from large datasets A Parameswaran, H Garcia-Molina, A Rajaraman Proceedings of the VLDB Endowment 3 (1-2), 566-577, 2010 | 109 | 2010 |
| Towards scalable dataframe systems D Petersohn, S Macke, D Xin, W Ma, D Lee, X Mo, JE Gonzalez, ... arXiv preprint arXiv:2001.00888, 2020 | 108 | 2020 |
hector garcia-molinaProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
