Graph indexing and querying: a review

International Journal of Web Information Systems

Volumn 6, Issue 2, 2010, Pages 101-120

  Sakr, Sherif ^a   Al Naymat, Ghazi ^a  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Databases; Graphical user interface; Indexing

Indexed keywords

DESIGN/METHODOLOGY/APPROACH; DIFFERENT MECHANISMS; FUTURE RESEARCH DIRECTIONS; MULTIMEDIA DATABASE; PROTEIN NETWORK; QUERYING MECHANISMS; RESEARCH ISSUES; TARGET APPLICATION;

DATABASE SYSTEMS; GRAPHICAL USER INTERFACES; QUERY PROCESSING; RESEARCH;

INDEXING (OF INFORMATION);

EID: 78649932793     PISSN: 17440084     EISSN: 1744092     Source Type: Journal    
DOI: 10.1108/17440081011053104     Document Type: Review

References (52)

1. Angles, R. and Gutiérrez, C. (2008), “Survey of graph database models”, ACM Computing Surveys, Vol. 40 No. 1, pp. 1-39.
2. Bruno, N., Chaudhuri, S. and Ramamurthy, R. (2009), “Power hints for query optimization”, Proceedings of the 25th International Conference on Data Engineering (ICDE), Shanghai, March 29-April 2, pp. 469-80.
3. Bunke, H. and Shearer, K. (1998), “A graph distance metric based on the maximal common subgraph”, Pattern Recognition Letters, Vol. 19 Nos 3-4, pp. 255-9.
4. Cai, D., Shao, Z., He, X., Yan, X. and Han, J. (2005), “Community mining from multi-relational networks”, Proceedings of the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), Porto, October 3-7, pp. 445-52.
5. Chen, C., Yan, X., Yu, P.S., Han, J., Zhang, D.-Q. and Gu, X. (2007), “Towards graph containment search and indexing”, Proceedings of the 33rd International Conference on Very Large Data Bases (VLDB), University of Vienna, September 23-27, pp. 926-37.
6. Cheng, J., Ke, Y. and Ng, W. (2009), “Efficient query processing on graph databases”, ACM Transactions of Database Systems (TODS), Vol. 34 No. 1.
7. Cheng, J., Ke, Y., Ng, W. and Lu, A. (2007), “FG-index: towards verification-free query processing on graph databases”, Proceedings of the ACM SIGMOD International Conference on Management of Data, Beijing, June 11-14, pp. 857-72.
8. Consens, M.P. and Mendelzon, A.O. (1990), “GraphLog: a visual formalism for real life recursion”, Proceedings of the Ninth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS), Nashville, TN, April 2-4, pp. 404-16.
9. Fernández, M.-L. and Valiente, G. (2001), “A graph distance metric combining maximum common subgraph and minimum common supergraph”, Pattern Recognition Letters, Vol. 22 Nos 6/7, pp. 753-8.
10. Fortin, S. (1996), The Graph Isomorphism Problem, Tech. Rep., Department of Computing Science, University of Alberta, Edmonton.
11. Gao, X., Xiao, B., Tao, D. and Li, X. (2010), “A survey of graph edit distance”, Pattern Analysis and Applications, Vol. 13 No. 1, pp. 113-29.
12. Garey, M.R. and Johnson, D.S. (1979), Computers and Intractability: A Guide to the Theory of NP-Completeness, W.H. Freeman, San Francisco, CA.
13. Giugno, R. and Shasha, D. (2002), “GraphGrep: a fast and universal method for querying graphs”, IEEE International Conference in Pattern Recognition (ICPR), pp. 112-15.
14. Guttman, A. (1984), “R-trees : a dynamic index structure for spatial searching”, Proceedings of the ACM SIGMOD International Conference on Management of Data, Boston, MA, pp. 47-57.
15. Gyssens, M., Paredaens, J., den Bussche, J.V. and Gucht, D.V. (1994), “A graph-oriented object database model”, IEEE Transactions of Knowledge and Data Engineering (TKDE), Vol. 6 No. 4, pp. 572-86.
16. He, H. and Singh, A.K. (2006), “Closure-tree: an index structure for graph queries”, Proceedings of the 22nd International Conference on Data Engineering (ICDE), Atlanta, GA, April 3-7, pp. 38-52.
17. Huan, J., Wang, W., Bandyopadhyay, D., Snoeyink, J., Prins, J. and Tropsha, A. (2004), “Mining protein family specific residue packing patterns from protein structure graphs”, Proceedings of the Eighth Annual International Conference on Computational Molecular Biology (RECOMB), San Diego, CA, March 27-31, pp. 308-15.
18. Jiang, H., Wang, H., Yu, P.S. and Zhou, S. (2007), “GString: a novel approach for efficient search in graph databases”, Proceedings of the 23rd International Conference on Data Engineering (ICDE), Istanbul, April 15-20, pp. 566-75.
19. Klinger, S. and Austin, J. (2005), “Chemical similarity searching using a neural graph matcher”, Proceedings of the 13th European Symposium on Artificial Neural Networks (ESANN), Bruges, April 27-29, pp. 479-84.
20. Kuramochi, M. and Karypis, G. (2001), “Frequent subgraph discovery”, Proceedings of the IEEE International Conference on Data Mining (ICDM), San Jose, CA, November 29-December 2, pp. 313-20.
21. Kuramochi, M. and Karypis, G. (2004), “GREW-A scalable frequent subgraph discovery algorithm”, Proceedings of the IEEE International Conference on Data Mining (ICDM), Brighton, November 1-4, pp. 439-42.
22. Kyoto Encyclopedia of Genes and Genomes (KEGG) (2010), available at: www.genome.jp/kegg/.
23. Lee, J., Oh, J.-H. and Hwang, S. (2005), “STRG-Index: spatio-temporal region graph indexing for large video databases”, Proceedings of the ACM SIGMOD International Conference on Management of Data, Baltimore, MD, June 14-16, pp. 718-29.
24. Manola, F. and Miller, E. (2004), “RDF primer: world wide web consortium proposed recommendation”, available at: www.w3.org/TR/rdf-primer/.
25. National Cancer Institute (NCI) (2010), available at: http://dtp.nci.nih.gov/.
26. Prud'hommeaux, E. and Seaborne, A. (2008), “SPARQL query language for RDF: world wide web consortium proposed recommendation”, available at: www.w3.org/TR/rdf-sparql-query/.
27. Raymond, J.W., Gardiner, E.J. and Willett, P. (2002), “RASCAL: calculation of graph similarity using maximum common edge subgraphs”, Computer Journal, Vol. 45 No. 6, pp. 631-44.
28. Sakr, S. (2009), “GraphREL: a decomposition-based and selectivity-aware relational framework for processing sub-graph queries”, Proceedings of the 14th International Conference on Database Systems for Advanced Applications (DASFAA), Brisbane, April 21-23, pp. 123-37.
29. Sakr, S. and Awad, A. (2010), “A framework for querying graph-based business process models”, Proceedings of the 19th International World Wide Web Conference (www), Raleigh, NC.
30. Sayed, A. (2009), “Fast and efficient computation of reachability queries over linked XML documents' graphs”, International Journal of Web Information Systems (IJWIS), Vol. 5 No. 1, pp. 56-76.
31. Sheng, L., Özsoyoglu, Z.M. and Özsoyoglu, G. (1999), “A graph query language and its query processing”, Proceedings of the 15th International Conference on Data Engineering (ICDE), IEEE Computer Society, Washington, DC, pp. 572-81.
32. Srinivasa, S., Maier, M., Mutalikdesai, M.R., Gowrishankar, K.A. and Gopinath, P.S. (2005), “LWI and safari: a new index structure and query model for graph databases”, Proceedings of the Eleventh International Conference on Management of Data (COMAD), Goa, January, pp. 138-47.
33. Stocker, M., Seaborne, A., Bernstein, A., Kiefer, C. and Reynolds, D. (2008), “SPARQL basic graph pattern optimization using selectivity estimation”, Proceedings of the 17th International Conference on World Wide Web (www), Beijing, pp. 595-604.
34. Teubner, J., Grust, T., Maneth, S. and Sakr, S. (2008), “Dependable cardinality forecasts for XQuery”, Proceedings of the VLDB Endowment (PVLDB), Auckland, August 23-28, Vol. 1 (1) pp. 463-77.
35. The Gene Ontology (2010), available at: www.geneontology.org/.
36. Tian, Y. and Patel, J.M. (2008), “TALE : a tool for approximate large graph matching”, Proceedings of the 24th International Conference on Data Engineering (ICDE), Cancún, April 7-12, pp. 963-72.
37. Tian, Y., McEachin, R.C., Santos, C., States, D.J. and Patel, J.M. (2007), “SAGA: a subgraph matching tool for biological graphs”, Bioinformatics, Vol. 23 No. 2, pp. 232-9.
38. Tian, Y., Patel, J.M., Nair, V., Martini, S. and Kretzler, M. (2008), “Periscope/GQ: a graph querying toolkit”, Proceedings of the VLDB Endowment (PVLDB), Vol. 1 No. 2, pp. 1404-7.
39. Wang, C., Wang, W., Pei, J., Zhu, Y. and Shi, B. (2004), “Scalable mining of large disk-based graph databases”, Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Seattle, Washington, DC, August 22-25, pp. 316-25.
40. Washio, T. and Motoda, H. (2003), “State of the art of graph-based data mining”, SIGKDD Explorations, Vol. 5 No. 1, pp. 59-68.
41. Westbrook, J.D., Feng, Z., Chen, L., Yang, H. and Berman, H.M. (2003), “The protein data bank and structural genomics”, Nucleic Acids Research, Vol. 31 No. 1, pp. 489-91.
42. Williams, D.W., Huan, J. and Wang, W. (2007), “Graph database indexing using structured graph decomposition”, Proceedings of the 23rd International Conference on Data Engineering (ICDE), Istanbul, pp. 976-85.
43. Yan, X. and Han, J. (2002), “gSpan: graph-based substructure pattern mining”, Proceedings of the IEEE International Conference on Data Mining (ICDM), Maebashi City, December 9-12, pp. 721-4.
44. Yan, X. and Han, J. (2003), “CloseGraph: mining closed frequent graph patterns”, Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), New York, NY, pp. 286-95.
45. Yan, X., Yu, P.S. and Han, J. (2004), “Graph indexing: a frequent structure-based approach”, Proceedings of the ACM SIGMOD International Conference on Management of Data, Paris, June 13-18, pp. 335-46.
46. Yan, X., Yu, P.S. and Han, J. (2005a), “Graph indexing based on discriminative frequent structure analysis”, ACM Transactions on Database Systems (TODS), Vol. 30 No. 4, pp. 960-93.
47. Yan, X., Yu, P.S. and Han, J. (2005b), “Substructure similarity search in graph databases”, Proceedings of the ACM SIGMOD International Conference on Management of Data, Baltimore, MD, June 14-16, pp. 766-77.
48. Yan, X., Zhu, F., Han, J. and Yu, P.S. (2006), “Searching substructures with superimposed distance”, Proceedings of the 22nd International Conference on Data Engineering (ICDE), Washington, DC, pp. 88-98.
49. Zhang, S., Hu, M. and Yang, J. (2007), “TreePi: a novel graph indexing method”, Proceedings of the 23rd International Conference on Data Engineering (ICDE), Istanbul, 15-20 April, pp. 966-75.
50. Zhang, S., Li, J., Gao, H. and Zou, Z. (2009), “A novel approach for efficient supergraph query processing on graph databases”, Proceedings of the 12th International Conference on Extending Database Technology (EDBT), Saint Petersburg, March 24-26, pp. 204-15.
51. Zhao, P., Yu, J.X. and Yu, P.S. (2007), “Graph indexing: tree+delta≥graph”, Proceedings of the 33rd International Conference on Very Large Data Bases (VLDB), Vienna, pp. 938-49.
52. Zou, L., Chen, L., Yu, J.X. and Lu, Y. (2008), “A novel spectral coding in a large graph database”, Proceedings of the 11th International Conference on Extending Database Technology (EDBT), Nantes, March 25-29, pp. 181-92.