Hypothetical Answers to Continuous Queries over Data Streams

Luís Cruz-Filipe, Isabel Nunes, Graça Gaspar
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Continuous queries over data streams often delay answers until some relevant input arrives through the data stream. These delays may turn answers, when they arrive, obsolete to users who sometimes have to make decisions with no help whatsoever. Therefore, it can be useful to provide hypothetical answers – "given the current information, it is possible that X will become true at time t" – instead of no information at all. In this paper we present a semantics for queries and corresponding answers
more » ... that covers such hypothetical answers, together with an online algorithm for updating the set of facts that are consistent with the currently available information.
doi:10.1609/aaai.v34i03.5668 fatcat:rpxcnzperzfrrpe2fd2pf7uwgy