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[x] M. Drosou and E. Pitoura. Ymaldb: a result-driven recommendation system for databases. In ICDT, 2013.
[ ] T. Milo and A. Somech. React: Context-sensitive recommendations for data analysis. In SIGMOD, 2016.
[ ] T. Milo and A. Somech. Next-step suggestions for modern interactive data analysis platforms. In KDD, 2018.
[ ] T. Milo, C. Ozeri, and A. Somech. Predicting "what is interesting" by mining interactive-data-analysis session logs. In EDBT, 2019.
[ ] K. Dimitriadou, O. Papaemmanouil, and Y. Diao. Aide: An active learning-based approach for interactive data exploration. TKDE, 2016.
[ ] E. Huang, L. Peng, L. D. Palma, A. Abdelkafi, A. Liu, and Y. Diao. Optimization for active learning-based interactive database exploration. Proceedings of the VLDB Endowment, 12(1):71–84, 2018.
[ ] Y. Luo, X. Qin, N. Tang, and G. Li. Deepeye: Towards automatic data visualization. ICDE, 2018.
[ ] V. Dibia and Ç. Demiralp. Data2vis: Automatic generation of data visualizations using sequence-to-sequence recurrent neural networks. IEEE computer graphics and applications, 39(5):33–46, 2019.
[ ] O. Bar El, T. Milo, and A. Somech. Atena: An autonomous system for data exploration based on deep reinforcement learning. In CIKM, 2019.
[ ] T. Milo and A. Somech. Deep reinforcement-learning framework for exploratory data analysis. In AIDM (at SIGMOD), page 4, 2018.
[ ] M. Drosou and E. Pitoura. Ymaldb: exploring relational databases via result-driven recommendations. VLDBJ, 22(6), 2013.
[x] M. Drosou and E. Pitoura. Ymaldb: a result-driven recommendation system for databases. In ICDT, 2013.
[ ] T. Milo and A. Somech. React: Context-sensitive recommendations for data analysis. In SIGMOD, 2016.
[ ] T. Milo and A. Somech. Next-step suggestions for modern interactive data analysis platforms. In KDD, 2018.
[ ] T. Milo, C. Ozeri, and A. Somech. Predicting "what is interesting" by mining interactive-data-analysis session logs. In EDBT, 2019.
[ ] K. Dimitriadou, O. Papaemmanouil, and Y. Diao. Aide: An active learning-based approach for interactive data exploration. TKDE, 2016.
[ ] E. Huang, L. Peng, L. D. Palma, A. Abdelkafi, A. Liu, and Y. Diao. Optimization for active learning-based interactive database exploration. Proceedings of the VLDB Endowment, 12(1):71–84, 2018.
[ ] Y. Luo, X. Qin, N. Tang, and G. Li. Deepeye: Towards automatic data visualization. ICDE, 2018.
[ ] V. Dibia and Ç. Demiralp. Data2vis: Automatic generation of data visualizations using sequence-to-sequence recurrent neural networks. IEEE computer graphics and applications, 39(5):33–46, 2019.
[ ] O. Bar El, T. Milo, and A. Somech. Atena: An autonomous system for data exploration based on deep reinforcement learning. In CIKM, 2019.
[ ] T. Milo and A. Somech. Deep reinforcement-learning framework for exploratory data analysis. In AIDM (at SIGMOD), page 4, 2018.