Aggregate Estimation in Hidden Databases with Checkbox Interfaces

A large number of Ib data repositories are hidden behind restrictive Ib interfaces, making it an important challenge to enable data analytics over these hidden Ib databases. Most existing techniques assume a form-like Ib interface which consists solely of categorical attributes (or numeric ones that can be discretized). Nonetheless, many real-world Ib interfaces (of hidden databases) also feature checkbox interfaces—e.g., the specification of a set of desired features, such as A/C, navigation, etc., for a carsearch Ibsite like Yahoo! Autos. I find that, for the purpose of data analytics, such checkbox-represented attributes differ fundamentally from the categorical/numerical ones that Ire traditionally studied. In this paper, I address the problem of data analytics over hidden databases with checkbox interfaces. Extensive experiments on both synthetic and real datasets demonstrate the accuracy and efficiency of our proposed algorithms.