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.
- A. Abouzied et al. Learning and verifying quantified boolean queries by example. arXiv.org {cs.DB}.Google Scholar
- A. Abouzied, J. Hellerstein, and A. Silberschatz. Dataplay: interactive tweaking and example-driven correction of graphical database queries. In UIST, 2012. Google Scholar
Digital Library
- D. Angluin. Queries and concept learning. Mach. Learn., 2(4):319--342, 1988. Google Scholar
Digital Library
- D. Angluin, M. Frazier, and L. Pitt. Learning conjunctions of horn clauses. In COLT, 1990. Google Scholar
Digital Library
- D. Angluin, L. Hellerstein, and M. Karpinski. Learning read-once formulas with queries. J. ACM, 40(1):185--210, 1993. Google Scholar
Digital Library
- M. Anthony et al. On exact specification by examples. In COLT, 1992. Google Scholar
Digital Library
- A. Das Sarma et al. Synthesizing view definitions from data. In ICDT, 2010. Google Scholar
Digital Library
- S. A. Goldman and M. J. Kearns. On the complexity of teaching. In COLT, 1991. Google Scholar
Digital Library
- J. Goldsmith and R. H. Sloan. New horn revision algorithms. J. Mach. Learn. Res., 6:1919--1938, Dec. 2005. Google Scholar
Digital Library
- D. Haussler. Learning conjunctive concepts in structural domains. Mach. Learn., 4(1):7--40, 1989. Google Scholar
Digital Library
- M. J. Kearns and U. V. Vazirani. An introduction to computational learning theory. MIT Press, Cambridge, MA, USA, 1994. Google Scholar
Digital Library
- R. Khardon. Learning first order universal horn expressions. In COLT, 1998. Google Scholar
Digital Library
- P. Reisner. Use of psychological experimentation as an aid to development of a query language. IEEE Trans. on Soft. Eng., SE-3(3):218--229, 1977. Google Scholar
Digital Library
- A. Shinohara and S. Miyano. Teachability in computational learning. New Gen. Comput., 8(4):337--347, 1991. Google Scholar
Digital Library
- S. Staworko and P. Wieczorek. Learning twig and path queries. In ICDT, 2012. Google Scholar
Digital Library
- B. ten Cate, V. Dalmau, and P. G. Kolaitis. Learning schema mappings. In ICDT, 2012. Google Scholar
Digital Library
- Q. T. Tran, C. Chan, and S. Parthasarathy. Query by output. In SIGMOD, 2009. Google Scholar
Digital Library
- L. G. Valiant. A theory of the learnable. CACM, 27(11):1134--1142, 1984. Google Scholar
Digital Library
Index Terms
Learning and verifying quantified boolean queries by example
Recommendations
Reverse Engineering SPJ-Queries from Examples
PODS '17: Proceedings of the 36th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database SystemsThis paper investigates the problem of reverse engineering, i.e., learning, select-project-join (SPJ) queries from a user-provided example set, containing positive and negative tuples. The goal is then to determine whether there exists a query returning ...
Learning a subclass of k-quasi-Horn formulas with membership queries
Boolean formulas have been widely studied in the field of learning theory. We focus on the model of learning with queries, and study a restriction of the class of k-quasi-Horn formulas, that is, conjunctive normal form formulas where the number of ...
A satisfiability procedure for quantified boolean formulae
The renesse issue on satisfiabilityWe present a satisfiability tester QSAT for quantified Boolean formulae and a restriction QSATCNF of QSAT to unquantified conjunctive normal form formulae. QSAT makes use of procedures which replace subformulae of a formula by equivalent formulae. By a ...






Comments