The Graph Traversal Pattern

@inproceedings{Rodriguez2011TheGT,
  title={The Graph Traversal Pattern},
  author={Michael A. Rodriguez and Peter Neubauer},
  booktitle={Graph Data Management},
  year={2011}
}
A graph is a structure composed of a set of vertices (i.e.nodes, dots) connected to one another by a set of edges (i.e.links, lines). The concept of a graph has been around since the late 19$^\text{th}$ century, however, only in recent decades has there been a strong resurgence in both theoretical and applied graph research in mathematics, physics, and computer science. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the… 

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References

SHOWING 1-10 OF 31 REFERENCES
Survey of graph database models
TLDR
The main objective of this survey is to present the work that has been conducted in the area of graph database modeling, concentrating on data structures, query languages, and integrity constraints.
Evaluating use of data flow systems for large graph analysis
TLDR
It is found that a dataflow system can achieve orders of magnitude performance improvement over state-of-art database systems and serve as a viable scalable graph analysis engine.
Dex: high-performance exploration on large graphs for information retrieval
TLDR
DEX is proposed and evaluated, a high performance graph database querying system that allows for the integration of multiple data sources and makes graph querying possible in different flavors, including link analysis, social network analysis, pattern recognition and keyword search.
Expressive languages for path queries over graph-structured data
TLDR
A class of extended CRPQs, called ECRPZs, are proposed, which add regular relations on tuples of paths, and allow path variables in the heads of queries, and study their properties.
Join processing in relational databases
TLDR
The different kinds of joins and the various implementation techniques are surveyed and they are classified based on how they partition tuples from different relations.
Graphs & Digraphs
Mapping Semantic Networks to Undirected Networks
TLDR
The semantic network construct does not have any modeling functionality that is not possible with either a directed or undirected network representation, and two proofs of this idea will be presented.
A new path algebra for finding paths in graphs
  • R. Manger
  • Mathematics, Computer Science
    26th International Conference on Information Technology Interfaces, 2004.
  • 2004
TLDR
A new path algebra is considered, which can be applied for finding one path between any pair of nodes in a graph, and it is proved that the proposed solution is correct and computationally efficient.
...
...