Ontology-Based Query Answering for Probabilistic Temporal Data

Talk by Patrick Koopmann

Location: APB 3027
Start: 17. January 2019 at 1:00 pm
End: 17. January 2019 at 2:30 pm
Research group: Automata Theory
Event series: KBS Seminar
iCal

Abstract: We investigate ontology-based query answering for data that are both temporal

and probabilistic, which might occur in contexts such as stream reasoning or situation recognition with uncertain data. We present a framework that allows to represent temporal probabilistic data, and introduce a query language with which complex temporal and probabilistic patterns can be described. Specifically, this language combines conjunctive queries with operators from linear time logic as well as probability operators. We analyse the complexities of evaluating queries in this language in various settings. While in some cases, combining the temporal and the probabilistic dimension in such a way comes at the cost of increased complexity, we also determine cases for which this increase can be avoided.

This is a talk based on a paper that will be presented at this year’s AAAI conference.