A surprising query result is often an indication of errors in
\nthe query or the underlying data. Recent work suggests us-
\ning causal reasoning to nd explanations for the surprising
\nresult. In practice, however, one often has multiple queries
\nand\/or multiple answers, some of which may be considered
\ncorrect and others unexpected. In this paper, we focus on
\ndetermining the causes of a set of unexpected results, pos-
\nsibly conditioned on some prior knowledge of the correct-
\nness of another set of results. We call this problem View-
\nConditioned Causality. We adapt the denitions of causa-
\nlity and responsibility for the case of multiple answers\/views
\nand provide a non-trivial algorithm that reduces the problem
\nof nding causes and their responsibility to a satisability
\nproblem that can be solved with existing tools. We evaluate
\nboth the accuracy and eectiveness of our approach on a real
\ndataset of user-generated mobile device tracking data, and
\ndemonstrate that it can identify causes of error more eec-
\ntively than static Boolean in
\nuence and alternative notions
\nof causality.<\/p>\n","protected":false},"excerpt":{"rendered":"
A surprising query result is often an indication of errors in the query or the underlying data. Recent work suggests us- ing causal reasoning to nd explanations for the surprising result. In practice, however, one often has multiple queries and\/or multiple answers, some of which may be considered correct and others unexpected. In this paper, […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-160923","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"ACM","msr_edition":"SIGMOD'11: Proceedings of the 2011 ACM SIGMOD international conference on Management of 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