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 …

Temporal graphs are widely used to model dynamic systems with time-varying interactions.
In real-world scenarios, the underlying mechanisms of generating future interactions in …

With the rapid development of information technologies, multi-source heterogeneous data
has become an open problem, and the data is usually modeled as graphs since the graph …

A graph stream, which refers to the graph with edges being updated sequentially in a form of
a stream, has important applications in cyber security and social networks. Due to the sheer …

Due to the growing need to process large graph and network datasets created by modern
applications, recent years have witnessed a surging interest in developing big graph …

Continuous subgraph matching (CSM) is an important building block in many real-time
graph processing applications. Given a subgraph query Q and a data graph stream, a CSM …

Continuous subgraph matching (CSM) algorithms find the occurrences of a given pattern on
a stream of data graphs online. A number of incremental CSM algorithms have been …

A dynamic graph is defined by an initial graph and a graph update stream consisting of edge
insertions and deletions. Identifying and monitoring critical patterns in the dynamic graph is …

A graph stream is a continuous sequence of data items, in which each item indicates an
edge, including its two endpoints and edge weight. It forms a dynamic graph that changes …

Graphs are commonly used for representing complex structures such as social relationships,
biological interactions, and knowledge bases. In many scenarios, graphs not only represent …