Composite event recognition (CER) systems process streams of sensor data and infer
composite events of interest by means of pattern matching. Data uncertainty is frequent in …

Complex Event Recognition (CER) systems detect event occurrences in streaming time-
stamped input using predefined event patterns. Logic-based approaches are of special …

We present an open-source system that can optimize compressed trajectory representations
for large fleets of vessels. We take into account the type of each vessel in order to choose a …

This tutorial presents a statistical relational extension of the answer set programming
language called LP MLN, which incorporates the concept of weighted rules into the stable …

Abstract Complex Event Recognition (CER) systems detect event occurrences in streaming
input using predefined event patterns. Techniques that learn event patterns from data are …

One of the challenges in Artificial Intelligence (AI) is to integrate fast, automatic, and intuitive
System-1 thinking with slow, deliberate, and logical System-2 thinking. While deep learning …

This paper presents the first automatic method for learning and revising dynamic temporal
theories in the full-fledged Discrete Event Calculus (DEC), where fluents may be temporarily …

Contemporary applications commonly demand the detection of 'situations of interest'in real-
time and with minimal latency. In maritime situational awareness, eg, it is crucial to identify …

Human activity recognition (HAR) is a fundamental task in artificial intelligence, with
applications in healthcare, smart homes, and surveillance. Traditional deep learning …

ABSTRACT Complex Event Recognition (CER) systems detect occurrences of complex
events (eg meeting, moving, dangerous driving) in a streaming time-stamped input of simple …