Talks and Poster Presentations (with Proceedings-Entry):

L. Bellomarini, M. Nissl, E. Sallinger:
"Monotonic Aggregation for Temporal Datalog";
Talk: RuleML+RR 2021, Leuven, Belgium; 2021-09-08 - 2021-09-15; in: "Proceedings of the 15th International Rule Challenge, 7th Industry Track, and 5th Doctoral Consortium @ RuleML+RR 2021 co-located with 17th Reasoning Web Summer School {(RW} 2021) and 13th DecisionCAMP 2021 as part of Declarative {AI} 2021, Leuven, Belgium (virtual due to Covid-19 pandemic), 8 - 15 September, 2021}", (2021), 1 - 23.

English abstract:
Understanding time-based effects has become an important
aspect for the analysis of Knowledge Graphs (KGs). We have seen this
in different areas such as IoT or economics. Scalable solutions for using
Datalog-based KGs with time are in their infancy and the usage together
with aggregation has not been considered so far. Yet, one needs both
aggregation and time-based analysis when analysing KGs such as those
of economic phenomena. In this paper, we analyze monotonic aggregation
over DatalogMTL, establishing the first work that covers full recursion
like in Datalog, aggregation, and temporal reasoning.

Knowledge Graphs Datalog Temporal Reasoning

Related Projects:
Project Head Reinhard Pichler:

Created from the Publication Database of the Vienna University of Technology.