A relational-based approach for aggregated search in graph databases

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7238 LNCS, Issue PART 1, 2012, Pages 33-47

  Le, Thanh Huy ^a   Elghazel, Haytham ^b   Hacid, Mohand Saíd ^a  

^a UNIVERSITÉ LYON 1   (France)

^b UNIVERSITÉ DE LYON   (France)

Author keywords

aggregated search; graph databases; query processing; relational databases

Indexed keywords

AGGREGATED SEARCH; FLEXIBLE FRAMEWORK; GRAPH DATABASE; GRAPH-BASED; JOIN OPERATION; QUERY CONSTRAINTS; RELATIONAL DATABASE; SINGLE GRAPH; SYNTHETIC DATASETS; USER QUERY;

ALGORITHMS; DATABASE SYSTEMS; QUERY PROCESSING;

AGGREGATES;

EID: 84860690353     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-29038-1_5     Document Type: Conference Paper

References (26)

1. Balmin, A., Papakonstantinou, Y.: Storing and querying xml data using denormalized relational databases. The VLDB Journal 14(1), 30-49 (2005)
2. Bonstrom, V., Hinze, A., Schweppe, H.: Storing rdf as a graph
3. Cai, D., Shao, Z., He, X., Yan, X., Han, J.: Community Mining from Multi-Relational Networks. In: Jorge, A.M., Torgo, L., Brazdil, P.B., Camacho, R., Gama, J. (eds.) PKDD 2005. LNCS (LNAI), vol. 3721, pp. 445-452. Springer, Heidelberg (2005)
4. Cheng, J., Ke, Y., Ng, W., Lu, A.: Fg-index: towards verification-free query processing on graph databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 857-872 (2007)
5. Dau, F.: RDF as Graph-Based, Diagrammatic Logic. In: Esposito, F., Raś, Z.W., Malerba, D., Semeraro, G. (eds.) ISMIS 2006. LNCS (LNAI), vol. 4203, pp. 332-337. Springer, Heidelberg (2006)
6. Elghazel, H., Hacid, M.-S.: Aggregated Search in Graph Databases: Preliminary Results. In: Jiang, X., Ferrer, M., Torsello, A. (eds.) GbRPR 2011. LNCS (LNAI), vol. 6658, pp. 92-101. Springer, Heidelberg (2011)
7. Giugno, R., Shasha, D.: Graphgrep: A fast and universal method for querying graphs. In: Proceedings of the International Conference on Pattern Recognition, pp. 112-115 (2002)
8. Kopliku, A., Pinel-Sauvagnat, K., Boughanem, M.: Aggregated search: potential, issues and evaluation. Technical Report RT2009-4FR, IRIT (2009), http://www.irit.fr/PERSONNEL/SIG/kopliku/
9. Neuhaus, M., Bunke, H.: Self-organizing maps for learning the edit costs in graph matching. IEEE Transactions on Systems, Man, and Cybernetics, Part B 35(3), 503-514 (2005)
10. Neuhaus, M., Bunke, H.: Automatic learning of cost functions for graph edit distance. Information Sciences 177(1), 239-247 (2007)
11. Petrakis, E.G.M., Faloutsos, C.: Similarity searching in medical image databases. IEEE Transactions on Knowledge and Data Engineering 9(3), 435-447 (1997)
12. Raymond, J.W., Gardiner, E.J., Willett, P.: Calculation of graph similarity using maximum common edge subgraphs. The Computer Journal 45, 631-644 (2002)
13. Riesen, K., Jiang, X., Bunke, H.: Exact and inexact graph matching: Methodology and applications. In: Aggarwal, C.C., Wang, H. (eds.) Managing and Mining Graph Data, pp. 217-247. Springer, US (2010)
14. Sakr, S.: Storing and Querying Graph Data using Efficient Relational Processing Techniques. In: Yang, J., Ginige, A., Mayr, H.C., Kutsche, R.-D. (eds.) Information Systems: Modeling, Development, and Integration. LNBIP, vol. 20, pp. 379-392. Springer, Heidelberg (2009)
15. Sakr, S., Al-Naymat, G.: Efficient relational techniques for processing graph queries. Journal of Computer Science and Technology 25(6), 1237-1255 (2010)
16. Sakr, S., Awad, A.: A framework for querying graph-based business process models. In: Proceedings of the 19th International Conference onWorldWideWeb (WWW), pp. 1297-1300. ACM, New York (2010)
17. Shang, H., Zhang, Y., Lin, X., Yu, J.X.: Taming verification hardness: an efficient algorithm for testing subgraph isomorphism. In: Proceedings of the International Conference on Very Large Data Bases, pp. 364-375 (2008)
18. Shasha, D., Wang, J.T.L., Giugno, R.: Algorithmics and applications of tree and graph searching. In: Proceedings of the Twenty-First ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS), pp. 39-52 (2002)
19. Tatarinov, I., Viglas, S.D., Beyer, K., Shanmugasundaram, J., Shekita, E., Zhang, C.: Storing and querying ordered xml using a relational database system. In: Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data, pp. 204-215 (2002)
20. Ullmann, J.R.: An algorithm for subgraph isomorphism. Journal of ACM 23(1), 31-42 (1976)
21. Willett, P., Barnard, J.M., Downs, G.M.: Chemical similarity searching. Journal of Chemical Information and Computer Sciences 38(6), 983-996 (1998)
22. Yan, X., Yu, P.S., Han, J.: Graph indexing: A frequent structure-based approach. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 335-346 (2004)
23. Yan, X., Yu, P.S., Han, J.: Substructure similarity search in graph databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 766-777 (2005)
24. Yang, Q., Sze, S.-H.: Path matching and graph matching in biological networks. Journal of Computational Biology 14(1), 56-67 (2007)
25. Zhang, S., Hu, M., Yang, J.: Treepi: A novel graph indexing method. In: Proceedings of the International Conference on Data Engineering, pp. 966-975 (2007)
26. Zhao, P., Yu, J.X., Yu, P.S.: Graph indexing: Tree + delta >= graph. In: Proceedings of the International Conference on Very Large Data Bases, pp. 938-949 (2007)