RDF data are used to model knowledge in various areas such as life sciences, Semantic
Web, bioinformatics, and social graphs. The size of real RDF data reaches billions of triples …

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 …

Subgraph matching is to find all subgraphs in a data graph that are isomorphic to an existing
query graph. Subgraph matching is an NP-hard problem, yet has found its applications in …

Subgraph matching is the task of finding all matches of a query graph in a large data graph,
which is known as an NP-complete problem. Many algorithms are proposed to solve this …

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 …

Money laundering refers to the criminal attempt of concealing the origins of illegally obtained
money, usually by passing it through a complex sequence of seemingly legitimate financial …

Queries to detect isomorphic subgraphs are important in graph-based data management.
While the problem of subgraph isomorphism search has received considerable attention for …

Graph-based text representation is one of the important preprocessing steps in data and text
mining, Natural Language Processing (NLP), and information retrieval approaches. The …

Subgraph matching is a fundamental problem in graph theory and has wide applications in
areas like sociology, chemistry, and social networks. Due to its NP-hardness, the basic …

Subgraph query processing (also known as subgraph search) and subgraph matching are
fundamental graph problems in many application domains. A lot of efforts have been made …