Using genetic algorithms to work out index configurations for the class-hierarchy indexing in object databases

Information and Software Technology

Volumn 42, Issue 11, 2000, Pages 731-741

  Song, H J ^a   Ahn, J H ^a   Kim, H J ^a  

^a Seoul National University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SYSTEMS PROGRAMMING; DATA STRUCTURES; GENETIC ALGORITHMS; INDEXING (OF INFORMATION); RESPONSE TIME (COMPUTER SYSTEMS);

CLASS-HIERARCHY INDEX; OBJECT DATABASES; PARTITION INDEX CONFIGURATION SCHEME;

DATABASE SYSTEMS;

EID: 0034249310     PISSN: 09505849     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0950-5849(00)00113-0     Document Type: Article

References (19)

1. Bertino E., Foscoli P. Index organizations for object-oriented database systems. IEEE Transactions on Knowledge and Database Engineering. 7:(2):1995;193-209.
2. Bertino E., Kim W. Indexing techniques for queries on nested objects. IEEE Transactions on Knowledge and Database Engineering. 1:(2):1989;196-214.
3. T.N. Bui, B.R. Moon, A fast and stable hybrid genetic algorithm for the ratio-cut partitioning problem on hypergraphs, in: Proceedings of the Design Automation Conference, 1994, pp. 664-669.
4. Bui T.N., Moon B.R. Genetic algorithm and graph partitioning. IEEE Transactions on Computers. 45:(7):1996;841-855.
5. I.T. Christou, R.R. Meyer, Fast distributed genetic algorithms for partitioning uniform grids, in: Proceedings of the Workshop on Parallel Algorithms for Irregularly Structured Problems, 1996, pp. 89-103.
6. Commer D. The ubiquitous b-tree. ACM Computing Surveys. 11:(2):1979;121-137.
7. I.W. Flockhart, N.J. Radcliffe, A genetic algorithm-based approach to data mining, in: Proceedings of Knowledge Discovery and Data Mining, 1996, pp. 299-302.
8. Goldberg D.E. Genetic Algorithms in Search, Optimization, and Machine Learning. 1989;Addison-Wesley, Reading, MA.
9. Postgres Global Development Group, PostgreSQL Programmer's Guide, 1999.
10. A. Guttman, R-trees: a dynamic index structure for spatial searching, in: Proceedings of the ACM SIGMOD International Conference on Management of Data, 1984, pp. 47-57.
11. J.T. Horng, B.J. Liu, A genetic algorithm for database query optimization, in: Proceedings of the First IEEE Conference on Evolutionary Computation, 1994, pp. 350-355.
12. Y. Ishikawa, H. Kitagawa, N. Ohbo, Evaluation of signature files as set access facilities in oodbs, in: Proceedings of the ACM SIGMOD International Conference on Management of Data, 1993, pp. 247-256.
13. C. Kilger, G. Moerkotte, Indexing multiple sets, in: Proceedings of the International Conference on Very Large Data Bases, 1994, pp. 180-191.
14. Kim W., Kim K.-C., Dale A. Object-oriented Concepts, Databases, and Applications. 1989;Addison-Wesley, Reading, MA. (Chapter: Indexing Techniques for Object-oriented Databases).
15. C.C. Low, B.C. Ooi, H. Lu, H-trees: a dynamic associative search index for oodb, in: Proceedings of the ACM SIGMOD International Conference on Management of Data, 1992, pp. 134-143.
16. S. Ramaswamy, P.C. Kanellakis, Oodb indexing by class-division, in: Proceedings of the ACM SIGMOD International Conference on Management of Data, 1995, pp. 139-150.
17. B. Sreenath, S. Seshadri, The hcc-tree: an efficient index structure for object oriented databases, in: Proceedings of the International Conference on Very Large Data Bases, 1992, pp. 203-213.
18. Srinivas M., Patnaik L.M. Genetic algorithms: a survey. IEEE Computer. 27:(6):1994;17-26.
19. P. van Bommel, Th.P. van der Weide, Towards database optimization by evolution, in: Proceedings of the International Conference on Information Systems and Management of Data (CISMOD), 1992, pp. 273-287.