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.
| Original language | English |
|---|---|
| Title of host publication | AAAI 2020 - 34th AAAI Conference on Artificial Intelligence |
| Number of pages | 8 |
| Publisher | AAAI Press |
| Publication date | 2020 |
| Pages | 2798-2805 |
| DOIs | |
| Publication status | Published - 2020 |
| Event | Conference on Artificial Intelligence - New York, United States Duration: 7 Feb 2020 → 12 Feb 2020 Conference number: 34 https://dblp.org/db/conf/aaai/aaai2020.html |
Conference
| Conference | Conference on Artificial Intelligence |
|---|---|
| Number | 34 |
| Country/Territory | United States |
| City | New York |
| Period | 07/02/2020 → 12/02/2020 |
| Internet address |
Keywords
- Data streams
- Continuous queries
- Hypothetical reasoning
- Online algorithms
- Epistemic semantics
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