GraphFind: enhancing graph searching by low support data mining techniques
2008
GraphFind: A New System for Graph Searching
Sample size: 40000
publication
Evidence: high
Author Information
Author(s): Ferro Alfredo, Giugno Rosalba, Mongiovì Misael, Pulvirenti Alfredo, Skripin Dmitry, Shasha Dennis
Primary Institution: Università di Catania
Hypothesis
Can low support data mining techniques enhance graph searching systems?
Conclusion
GraphFind outperforms existing systems in graph searching and significantly reduces index size.
Supporting Evidence
- GraphFind allows users to select candidate subgraphs rather than entire graphs.
- Experiments show that GraphFind outperforms the compared systems on a very large collection of small graphs.
- The proposed low-support mining technique allows a significant index space reduction.
Takeaway
GraphFind is a tool that helps find patterns in graphs, like searching for shapes in a big picture, and it does this really well by using smart tricks to save space.
Methodology
GraphFind uses efficient graph searching algorithms and low-support data mining techniques to improve performance.
Limitations
The system's performance may vary based on the size and complexity of the graphs being searched.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website