Graph summarization methods and applications: A survey
While advances in computing resources have made processing enormous amounts of data
possible, human ability to identify patterns in such data has not scaled accordingly. Efficient …
possible, human ability to identify patterns in such data has not scaled accordingly. Efficient …
Survey and taxonomy of lossless graph compression and space-efficient graph representations
Various graphs such as web or social networks may contain up to trillions of edges.
Compressing such datasets can accelerate graph processing by reducing the amount of I/O …
Compressing such datasets can accelerate graph processing by reducing the amount of I/O …
Summarizing semantic graphs: a survey
The explosion in the amount of the available RDF data has lead to the need to explore,
query and understand such data sources. Due to the complex structure of RDF graphs and …
query and understand such data sources. Due to the complex structure of RDF graphs and …
Truss-based community search: a truss-equivalence based indexing approach
We consider the community search problem defined upon a large graph G: given a query
vertex q in G, to find as output all the densely connected subgraphs of G, each of which …
vertex q in G, to find as output all the densely connected subgraphs of G, each of which …
Graph cube: on warehousing and OLAP multidimensional networks
We consider extending decision support facilities toward large sophisticated networks, upon
which multidimensional attributes are associated with network entities, thereby forming the …
which multidimensional attributes are associated with network entities, thereby forming the …
A comprehensive survey on graph reduction: Sparsification, coarsening, and condensation
Many real-world datasets can be naturally represented as graphs, spanning a wide range of
domains. However, the increasing complexity and size of graph datasets present significant …
domains. However, the increasing complexity and size of graph datasets present significant …
Graph summarization with quality guarantees
We study the problem of graph summarization. Given a large graph we aim at producing a
concise lossy representation (a summary) that can be stored in main memory and used to …
concise lossy representation (a summary) that can be stored in main memory and used to …
The atlas for the aspiring network scientist
Network science is the field dedicated to the investigation and analysis of complex systems
via their representations as networks. We normally model such networks as graphs: sets of …
via their representations as networks. We normally model such networks as graphs: sets of …
Clustering and summarizing protein-protein interaction networks: A survey
The increasing availability and significance of large-scale protein-protein interaction (ppi)
data has resulted in a flurry of research activity to comprehend the organization, processes …
data has resulted in a flurry of research activity to comprehend the organization, processes …
Wonderland: A novel abstraction-based out-of-core graph processing system
Many important graph applications are iterative algorithms that repeatedly process the input
graph until convergence. For such algorithms, graph abstraction is an important technique …
graph until convergence. For such algorithms, graph abstraction is an important technique …