Stream reasoning studies the application of inference techniques to data characterised by
being highly dynamic. It can find application in several settings, from Smart Cities to Industry …

Event processing (EP) is a data processing technology that conducts online processing of
event information. In this survey, we summarize the latest cutting-edge work done on EP …

Dynamic networks are used in a wide range of fields, including social network analysis,
recommender systems and epidemiology. Representing complex networks as structures …

Traditional online algorithms encapsulate decision making under uncertainty, and give ways
to hedge against all possible future events, while guaranteeing a nearly optimal solution, as …

A hands-on approach to tasks and techniques in data stream mining and real-time analytics,
with examples in MOA, a popular freely available open-source software framework. Today …

In the model of online caching with machine learned advice, introduced by Lykouris and
Vassilvitskii, the goal is to solve the caching problem with an online algorithm that has …

Given a stream of heterogeneous graphs containing different types of nodes and edges,
how can we spot anomalous ones in real-time while consuming bounded memory? This …

The algorithms community has been modeling the underlying key features and constraints of
massively parallel frameworks and using these models to discover new algorithmic …

How do we spot interesting events from e-mail or transportation logs? How can we detect
port scan or denial of service attacks from IP-IP communication data? In general, given a …

Graph processing is increasingly bottlenecked by main memory accesses. On-chip caches
are of little help because the irregular structure of graphs causes seemingly random memory …