This tutorial presents the formal methods for Complex Event Recognition (CER), i.e. models based on automata and computational logic, as they have been developed in the database, distributed systems, and artificial intelligence communities.

This tutorial shows how formal methods from automata theory and computational logic provide a sound and effective approach to complex event processing in the Big Data era.

The Complex Event Recognition (CER) group of NCSR “Demokritos” works towards advanced and efficient methods for the recognition of complex events in a multitude of large, heterogeneous and interdependent data streams.

The goal of this tutorial is to provide a step-by-step guide for realizing CER in the Big Data era.

A summary of the most prominent models and algorithms for Complex Event Recognition.

In this tutorial, we review complex event recognition technologies. We focus on the Chronicle Recognition System (CRS), the Event Calculus (EC), ProbLog and Markov Logic Networks (MLN).

We review a Chronicle Recognition System (CRS), the Event Calculus (EC), ProbLog and Markov Logic Networks (MLN).