Abstract Large temporal Databases (TDBs) usually contain a wealth of data about temporal events. Aimed at discovering temporal patterns with during relationship (during-temporal pa...
— We introduce a graph-based relational learning approach using graph-rewriting rules for temporal and structural analysis of biological networks changing over time. The analysis...
This paper presents an extension of Petri net framework with imprecise temporal properties. We use possibility theory to represent imprecise time by time-stamping tokens and assig...
—Rule-based filters are sequences of rules formed of a condition and a decision. Rules are applied sequentially up to the first fulfilled condition, whose matching decision de...
In this paper we study how the framework of Petri nets can be extended and applied to study recurrent events. We use possibility theory to realistically model temporal properties o...