Incremental learning, online learning, and data stream learning are terms commonly
associated with learning algorithms that update their models given a continuous influx of …

Increasing supply chain complexity poses new challenges to managers. On the other hand,
evolving information and communication technology offers ample opportunity for more …

Pattern matching over event streams is increasingly being employed in many areas
including financial services, RFIDbased inventory management, click stream analysis, and …

Efficient matching of incoming events to persistent queries is fundamental to event pattern
matching, complex event processing, and publish/subscribe systems. Recent processing …

Achieving low latency in time-order real-time event stream processing of data produced by a
large number of IoT devices is difficult due to the buffering time required for sorting event …

Process mining is no longer limited to the one-off analysis of static event logs extracted from
a single enterprise system. Rather, process mining may strive for immediate insights based …

In event stream applications, events flow through a network of components that perform
various types of operations, eg, filtering, aggregation, transformation. When the operation …

Embodiments relate to a concept for ordering events of an event stream, comprising out-of-
order events, for an event detector, wherein the events have associated thereto individual …

Event-based Systems (EBS) are used to detect and analyze meaningful events in
surveillance, sports, finances and many other areas. With rising data and event rates and …

This article addresses the question of what properties can be monitored over an unreliable
communication channel. We model unreliable communications as mutations to finite traces …