PLAIMay 23, 2019

Hypothetical answers to continuous queries over data streams

arXiv:1905.09610v31.2
Originality Synthesis-oriented
AI Analysis

This addresses the issue of obsolete or missing answers for users needing real-time decisions in data stream applications, but it appears incremental as it builds on existing query semantics.

The paper tackles the problem of delays in continuous queries over data streams by introducing hypothetical answers to provide timely information, resulting in a semantics and online algorithm for updating consistent facts.

Continuous queries over data streams may suffer from blocking operations and/or unbound wait, which may 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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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