Enormous amounts of data are being produced everyday by sub-meters and smart sensors
installed in residential buildings. If leveraged properly, that data could assist end-users …

Event sequence data record series of discrete events in the time order of occurrence. They
are commonly observed in a variety of applications ranging from electronic health records to …

This paper provides a comprehensive survey of anomaly detection for the Internet of Things
(IoT). Anomaly detection poses numerous challenges in IoT, with broad applications …

Abstract Explainable Artificial Intelligence (XAI) develops technical explanation methods and
enable interpretability for human stakeholders on why Artificial Intelligence (AI) and machine …

Event sequence data is increasingly available in various application domains, such as
business process management, software engineering, or medical pathways. Processes in …

Anomaly detection for discrete event logs can provide critical information for building secure
and reliable systems in various application domains, such as large scale data centers …

Business process management distinguishes the actual “as-is” and a prescribed “to-be”
state of a process. In practice, many different causes trigger a process's drifting away from its …

Background Deep learning models have attracted significant interest from health care
researchers during the last few decades. There have been many studies that apply deep …

Event sequence data is a special type of time-dependent data that captures information
about the order in which discrete events occur. The time-dimension is one of the factors that …

Anomaly detection is a common analytical task that aims to identify rare cases that differ from
the typical cases that make up the majority of a dataset. When analyzing event sequence …