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Hypothetical answers to continuous queries over data streams

  • Luís Cruz-Filipe
    ,
  • Graça Gaspar
    ,
  • Isabel Nunes
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Research
Peer-review

Abstract

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 that covers such hypothetical answers, together with an online algorithm for updating the set of facts that are consistent with the currently available information.

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Research
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 2798-2805 (8 pages)

Publication milestones

  • Published - 2020

Publication status

Published - 2020

Publisher

AAAI Press, United States

Publication IDs

  • Scopus: 85106410962

Host publication title

AAAI 2020 - 34th AAAI Conference on Artificial Intelligence

Publication metrics

PlumX, opens in new tab

Citation count
1
Captures
1
Mentions
1

Related Event

Title

Conference on Artificial Intelligence

Event type

Conference

Degree of recognition

International event

Date

07/02/2020 - 12/02/2020

Location

New YorkUnited States