GraphFind

Enhancing graph searching by low support data mining techniques

Alfredo Ferro, Rosalba Giugno, Misael Mongiovì, Alfredo Pulvirenti, Dmitry Skripin, Dennis Shasha

Research output: Contribution to journalArticle

Abstract

Background: Biomedical and chemical databases are large and rapidly growing in size. Graphs naturally model such kinds of data. To fully exploit the wealth of information in these graph databases, a key role is played by systems that search for all exact or approximate occurrences of a query graph. To deal efficiently with graph searching, advanced methods for indexing, representation and matching of graphs have been proposed. Results: This paper presents GraphFind. The system implements efficient graph searching algorithms together with advanced filtering techniques that allow approximate search. It allows users to select candidate subgraphs rather than entire graphs. It implements an effective data storage based also on low-support data mining. Conclusions: GraphFind is compared with Frowns, GraphGrep and gIndex. Experiments show that GraphFind outperforms the compared systems on a very large collection of small graphs. The proposed low-support mining technique which applies to any searching system also allows a significant index space reduction.

Original languageEnglish (US)
Article numberS10
JournalBMC Bioinformatics
Volume9
Issue numberSUPPL. 4
DOIs
StatePublished - Apr 25 2008

Fingerprint

Chemical Databases
Graph Searching
Data Mining
Information Storage and Retrieval
Data mining
Databases
Graph in graph theory
Data storage equipment
Data Storage
Graph Model
Indexing
Experiments
Subgraph
Mining
Filtering
Entire
Query
Experiment

ASJC Scopus subject areas

  • Medicine(all)
  • Structural Biology
  • Applied Mathematics

Cite this

GraphFind : Enhancing graph searching by low support data mining techniques. / Ferro, Alfredo; Giugno, Rosalba; Mongiovì, Misael; Pulvirenti, Alfredo; Skripin, Dmitry; Shasha, Dennis.

In: BMC Bioinformatics, Vol. 9, No. SUPPL. 4, S10, 25.04.2008.

Research output: Contribution to journalArticle

Ferro, A, Giugno, R, Mongiovì, M, Pulvirenti, A, Skripin, D & Shasha, D 2008, 'GraphFind: Enhancing graph searching by low support data mining techniques', BMC Bioinformatics, vol. 9, no. SUPPL. 4, S10. https://doi.org/10.1186/1471-2105-9-S4-S10
Ferro, Alfredo ; Giugno, Rosalba ; Mongiovì, Misael ; Pulvirenti, Alfredo ; Skripin, Dmitry ; Shasha, Dennis. / GraphFind : Enhancing graph searching by low support data mining techniques. In: BMC Bioinformatics. 2008 ; Vol. 9, No. SUPPL. 4.
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