A simple graph embedding for anomaly detection in a stream of heterogeneous labeled graphs
S Lagraa, K Amrouche, H Seba - Pattern Recognition, 2021 - Elsevier
In this work, we propose a new approach to detect anomalous graphs in a stream of directed
and labeled heterogeneous edges. The stream consists of a sequence of edges derived …
and labeled heterogeneous edges. The stream consists of a sequence of edges derived …
Similarity search in graph databases: A multi-layered indexing approach
We consider in this paper the similarity search problem that retrieves relevant graphs from a
graph database under the well-known graph edit distance (GED) constraint. Formally, given …
graph database under the well-known graph edit distance (GED) constraint. Formally, given …
An efficient graph indexing method
Graphs are popular models for representing complex structure data and similarity search for
graphs has become a fundamental research problem. Many techniques have been …
graphs has become a fundamental research problem. Many techniques have been …
Efficient graph similarity search over large graph databases
Since many graph data are often noisy and incomplete in real applications, it has become
increasingly important to retrieve graphs g in the graph database D that approximately …
increasingly important to retrieve graphs g in the graph database D that approximately …
GHashing: Semantic graph hashing for approximate similarity search in graph databases
Graph similarity search aims to find the most similar graphs to a query in a graph database
in terms of a given proximity measure, say Graph Edit Distance (GED). It is a widely studied …
in terms of a given proximity measure, say Graph Edit Distance (GED). It is a widely studied …
How to build templates for RDF question/answering: An uncertain graph similarity join approach
A challenging task in the natural language question answering (Q/A for short) over RDF
knowledge graph is how to bridge the gap between unstructured natural language …
knowledge graph is how to bridge the gap between unstructured natural language …
When subgraph isomorphism is really hard, and why this matters for graph databases
The subgraph isomorphism problem involves deciding whether a copy of a pattern graph
occurs inside a larger target graph. The non-induced version allows extra edges in the …
occurs inside a larger target graph. The non-induced version allows extra edges in the …
Grand: A fast and accurate graph retrieval framework via knowledge distillation
Graph retrieval aims to find the most similar graphs in a graph database given a query
graph, which is a fundamental problem with many real-world applications in chemical …
graph, which is a fundamental problem with many real-world applications in chemical …
CSI_GED: An efficient approach for graph edit similarity computation
Graph similarity is a basic and essential operation in many applications. In this paper, we
are interested in computing graph similarity based on edit distance. Existing graph edit …
are interested in computing graph similarity based on edit distance. Existing graph edit …
Efficient graph similarity joins with edit distance constraints
Graphs are widely used to model complicated data semantics in many applications in
bioinformatics, chemistry, social networks, pattern recognition, etc. A recent trend is to …
bioinformatics, chemistry, social networks, pattern recognition, etc. A recent trend is to …