Answering Why-questions by Exemplars in Attributed Graphs

This paper studies the problem of answering Why-questions for graph pattern queries. Given a query Q, its answers Q(G) in a graph G, and an exemplar 8 that describes desired answers, it aims to compute a query rewrite Q', such that Q'(G) incorporates relevant entities and excludes irrelevant ones wrt. 8 under a closeness measure. (1) We characterize the problem by Q-Chase. It rewrites Q by applying a sequence of applicable operators guided by 8, and backtracks to derive optimal query rewrite. (2) We develop feasible Q-Chase -based algorithms, from anytime solutions to fixed -parameter approximations to compute query rewrites. These algorithms implement Q -Chase by detecting picky operators at run time, which discriminately enforce 8 to retain answers that are closer to exemplars, and effectively prune both operators and irrelevant matches, by consulting a cache of star patterns (called star views). Using real -world graphs, we experimentally verify the efficiency and effectiveness of Q -Chase techniques and their applications.