Ranking Desired Tuples by Database Exploration

Database exploration – the problem of finding and ranking desired tuples – is important for data discovery and analysis. Precisely specifying SQL queries is not always feasible in practice, such as "finding and ranking off-road cars based on a combination of Price, Make, Model, Age, and Mileage." – not only due to the query complexity (e.g., which may have many if-then-else, and, or and not logic), but also because the user typically does not have the knowledge of all data instances.We propose DExPlorer, a system for interactive database exploration. DExPlorer offers a simple and user-friendly interface which allows to: (1) confirm whether a tuple is desired or not, and (2) decide whether a tuple is more preferred than another. Behind the scenes, we jointly use multiple ML models to learn from the above two types of user feedback. Moreover, in order to effectively involve users, we carefully select the set of tuples for which we need to solicit feedback. Therefore, we devise question selection algorithms that consider not only the estimated benefit of each tuple, but also the possible partial orders between any two suggested tuples. Experiments on real-world datasets show that DExPlorer is more effective than existing approaches.