Efficient Computation of Polynomial Explanations of Why-Not Questions

Nicole Bidoit 1, 2, 3, 4 Melanie Herschel 5 Aikaterini Tzompanaki 2, 3, 4, 1
3 OAK - Database optimizations and architectures for complex large data
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : Answering a Why-Not question consists in explaining why a query result does not contain some expected data, called missing answers. This paper focuses on processing Why-Not questions in a query-based approach that identifies the culprit query components. Our first contribution is a general definition of a Why-Not explanation by means of a polynomial. Intuitively, the polynomial provides all possible explanations to explore in order to recover the missing answers, together with an estimation of the number of recoverable answers. Moreover, this formalism allows us to represent Why-Not explanations in a unified way for extended relational models with probabilistic or bag semantics. We further present an algorithm to efficiently compute the polynomial for a given Why-Not question. An experimental evaluation demonstrates the practicality of the solution both in terms of efficiency and explanation quality, compared to existing algorithms.
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Nicole Bidoit, Melanie Herschel, Aikaterini Tzompanaki. Efficient Computation of Polynomial Explanations of Why-Not Questions. 24th ACM International Conference on Information and Knowledge Management - CIKM 2015, Oct 2015, Melbourne, Australia. ⟨10.1145/2806416.2806426⟩. ⟨hal-01182101⟩

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