This survey article presents a comprehensive and conceptual overview of anomaly detection
(AD) using dynamic graphs. We focus on existing graph-based AD techniques and their …

Anomaly detection is a crucial task in complex distributed systems. A thorough
understanding of the requirements and challenges of anomaly detection is pivotal to the …

Community search has been extensively studied in the past decades. In recent years, there
is a growing interest in attributed community search that aims to identify a community based …

Knowledge graphs (KGs) such as DBpedia, Freebase, YAGO, Wikidata, and NELL were
constructed to store large-scale, real-world facts as (subject, predicate, object) triples-that …

Cohesive subgraph mining on attributed social networks is attracting much attention in the
realm of graph mining and analysis. Most existing studies on cohesive subgraph mining …

Attributed Heterogeneous Information Networks (AHINs) amalgamate the advantages of
attributed graphs (AGs) and heterogeneous information networks (HINs) to model intri-cate …

Path querying refers to the evaluation of path queries in a graph database. New research in
this topic is crucial for the development of graph database systems as path queries are …

Graph is a generic model of various networks in real-world applications. And, graph
embedding aims to represent nodes (edges or graphs) as low-dimensional vectors which …

What is the widest community in which a person exercises a strong impact? Although
extensive attention has been devoted to searching communities containing given …

An Outstanding Fact (OF) is an attribute that makes a target entity stand out from its peers.
The mining of OFs has important applications, especially in Computational Journalism, such …