Leveraging efficient indexing schema to support multigraph query answering

  title={Leveraging efficient indexing schema to support multigraph query answering},
  author={Vijay Ingalalli and Dino Ienco and Pascal Poncelet},
  journal={Ing{\'e}nierie des Syst{\`e}mes d Inf.},
Many real world datasets can be represented by graphs with a set of nodes intercon- nected with each other by multiple relations (e.g., social network, RDF graph, biological data). Such a rich graph, called multigraph, is well suited to represent real world scenarios with com- plex interactions. However, performing subgraph query on multigraphs is still an open issue since, unfortunately, all the existing algorithms for subgraph query matching are not able to ad- equately leverage the multiple… 


On graph query optimization in large networks
The experimental studies demonstrate the effectiveness and scalability of SPath, which proves to be a more practical and efficient indexing method in addressing graph queries on large networks.
Fg-index: towards verification-free query processing on graph databases
A novel indexing technique that constructs a nested inverted-index, called FG- index, based on the set of Frequent subGraphs (FGs), which returns the exact set of query answers without performing candidate verification and is orders of magnitude more efficient than using the state-of-the-art graph index.
Graph indexing: a frequent structure-based approach
The gIndex approach not only provides and elegant solution to the graph indexing problem, but also demonstrates how database indexing and query processing can benefit form data mining, especially frequent pattern mining.
Turboiso: towards ultrafast and robust subgraph isomorphism search in large graph databases
This paper presents an efficient and robust subgraph search solution, called TurboISO, which is turbo-charged with two novel concepts, candidate region exploration and the combine and permute strategy (in short, Comb/Perm).
Efficient processing of graph similarity queries with edit distance constraints
Efficient algorithms are proposed to handle three types of graph similarity queries by exploiting both matching and mismatching features as well as degree information to improve the filtering and verification on candidates.
An In-depth Comparison of Subgraph Isomorphism Algorithms in Graph Databases
Five state-of-the-art subgraph isomorphism algorithms in a common code base are implemented and compared by comparing them using many real-world datasets and their query loads and report surprising empirical findings.
Trial for RDF: adapting graph query languages for RDF data
The goal is to introduce languages that work directly over triples and are closed, i.e., they produce sets of triples, rather than graphs, and compares them with relational languages, such as finite-variable logics, and previously studied graph query languages such as adaptations of XPath, regular path queries, and nested regular expressions.
Graphs-at-a-time: query language and access methods for graph databases
A graph algebra extended from the relational algebra in which the selection operator is generalized to graph pattern matching and a composition operator is introduced for rewriting matched graphs is presented and access methods of the selectionoperator are investigated.
Exploiting Vertex Relationships in Speeding up Subgraph Isomorphism over Large Graphs
This work proposes a novel approach, BoostIso, to reduce duplicate computation in subgraph isomorphism algorithms, and shows that it can be speeded up significantly, especially for some graphs with intensive vertex relationships, where the improvement can be up to several orders of magnitude.