Learning and verifying quantified boolean queries by example

Authors:
Azza Abouzied;Dana Angluin;Christos Papadimitriou;Joseph M. Hellerstein;Avi Silberschatz
Affiliations:
Yale University, New Haven, CT, USA;Yale University, New Haven, CT, USA;University of California, Berkeley, Berkeley, CA, USA;University of California, Berkeley, Berkeley, CA, USA;Yale University, New Haven, CT, USA
Venue:
Proceedings of the 32nd symposium on Principles of database systems
Year:
2013

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Abstract

To help a user specify and verify quantified queries --- a class of database queries known to be very challenging for all but the most expert users --- one can question the user on whether certain data objects are answers or non-answers to her intended query. In this paper, we analyze the number of questions needed to learn or verify qhorn queries, a special class of Boolean quantified queries whose underlying form is conjunctions of quantified Horn expressions. We provide optimal polynomial-question and polynomial-time learning and verification algorithms for two subclasses of the class qhorn with upper constant limits on a query's causal density.