Metaqueries: Semantics, complexity, and efficient algorithms

Artificial Intelligence

Volumn 149, Issue 1, 2003, Pages 61-87

  Ben Eliyahu Zohary, Rachel ^a   Gudes, Ehud ^a   Ianni, Giovambattista ^b  

^a BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

^b UNIVERSITY OF CALABRIA   (Italy)

Author keywords

Data mining; Knowledge discovery; Metaqueries; Support

Indexed keywords

ALGORITHMS; DATA MINING; DATABASE SYSTEMS; KNOWLEDGE BASED SYSTEMS; QUERY LANGUAGES; REAL TIME SYSTEMS; SEMANTICS;

METAQUERIES;

ARTIFICIAL INTELLIGENCE;

EID: 0042388782     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0004-3702(03)00073-0     Document Type: Article

References (23)

1. Agrawal R., Imielinski T., Swami A.N. Mining association rules between sets of items in large databases. Buneman P., Jajodia S. Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, Washington, DC. 1993;207-216 ACM Press, New York.
2. Agrawal R., Srikant R. Fast algorithms for mining association rules in large databases. Bocca J.B., Jarke M., Zaniolo C. Proceedings of 20th International Conference on Very Large Data Bases, VLDB'94, Santiago de Chile, Chile. 1994;487-499 Morgan Kaufmann, San Mateo, CA.
3. Angiulli F., Ben-Eliyahu-Zohary R., Ianni G.B., Palopoli L. Computational properties of metaquerying problems. ACM Transactions on Computational Logic (TOCL). 4:(2):2003;149-180. A short version in: Proceedings of PODS-2000, Dallas, TX, 2000, pp. 237-244.
4. Angiulli F., Ben-Eliyahu-Zohary R., Ianni G.B., Palopoli L. Computational properties of metaquerying problems. ACM Transactions on Computational Logic (TOCL). 4:(2):2003;149-180. A short version in: Proceedings of PODS-2000, Dallas, TX, 2000, pp. 237-244.
5. Ben-Eliyahu-Zohary R., Domshlak C., Gudes E., Liusternik N., Meisels A., Rosen T., Shimony S.E. FlexiMine - A flexible platform for KDD research and application construction. Ann. Math. Artificial Intelligence. 2003;. in press. A short version in: Proceedings of the Fourth International Conference on Knowledge Discovery in Databases (KDD-98), New York, 1998, pp. 184-188.
6. Ben-Eliyahu-Zohary R., Domshlak C., Gudes E., Liusternik N., Meisels A., Rosen T., Shimony S.E. FlexiMine - A flexible platform for KDD research and application construction. Ann. Math. Artificial Intelligence. 2003;. in press. A short version in: Proceedings of the Fourth International Conference on Knowledge Discovery in Databases (KDD-98), New York, 1998, pp. 184-188.
7. Chandra A.K., Merlin P.M. Optimal implementation of conjunctive queries in relational data bases. Conference Record of the Ninth Annual ACM Symposium on Theory of Computing, Boulder, CO. 1977;77-90.
8. Cheung D.W.-L., Han J. Maintenance of discovered knowledge: A strategy for updating association rules (abstract). Proceedings of the DOOD'95 Post-Conference Workshops on Integration of Knowledge Discovery in Databases with Deductive and Object-Oriented Databases (KDOOD) and Temporal Reasoning in Deductive and Object-Oriented Databases (TDOOD), Singapore. 1995.
9. Cheung D.W.-L., Han J., Ng V., Fu A.W.-C., Fu Y. A fast distributed algorithm for mining association rules. Proceedings of the Fourth International Conference on Parallel and Distributed Information Systems, Miami Beach, FL. 1996;31-42 IEEE Computer Society.
10. Cheung D.W.-L., Lee S.D., Kao B. A general incremental technique for maintaining discovered association rules. Topor R.W., Tanaka K. Database Systems for Advanced Applications'97, Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA), Melbourne, Australia. Advanced Database Research and Development Series. 6:1997;185-194 World Scientific, Singapore.
11. Dechter R. Enhancement schemes for constraint processing: Backjumping, learning, and cutset decomposition. Artificial Intelligence. 41:1990;273-312.
12. Dechter R. Constraint networks. Shapiro S.C. Encyclopedia of Artificial Intelligence. 2nd Edition: 1992;276-285 Wiley, New York.
13. Dietrich S.W. Extension tables: Memo relations in logic programming. Proceedings of the Symposium on Logic Programming, San Francisco, CA. 1987;264-272.
14. Dzeroski S., Muggleton S., Russell S. Pac-learnability of determinate logic programs. Proceedings of the Fifth ACM Workshop on Computational Learning Theory, New York. 1992;128-135.
15. Fayyad U., Piatetsky-Shapiro G., Smyth P., Uthurusamy R. Advances in Knowledge Discovery and Data Mining. 1996;AAAI Press/MIT Press, Cambridge, MA.
16. Garey M.R., Johnson D.S. Computers and Intractability, A Guide to the Theory of NP-Completeness. 1979;W.H. Freeman, New York.
17. Kamber M., Han J., Chiang J.Y. Metarule-guided mining of multi-dimensional association rules using data cubes. Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining, Newport Beach, CA. 1997.
18. Klemettinen M., Mannila H., Ronkainen P., Toivonen H., Verkamo A.I. Finding interesting rules from large sets of discovered association rules. Proceedings of 3rd Internat. Conf. on Information and Knowledge Management, Gaithersburg, MD. 1994;401-408.
19. Mitchell T.M. Machine Learning. 1997;McGraw-Hill Higher Education, New York.
20. Shen W.M. Discovering regularities from knowledge bases. Intelligent Systems. 7:(7):1992;623-636.
21. Shen W.-M., Leng B. A metapattern-based automated discovery loop for integrated data mining- unsupervised learning of relational patterns. IEEE Trans. Knowledge Data Engineering. 8:(6):1996;898-910.
22. Shen W.-M., Ong B.M.K., Zaniolo C. Metaqueries for data mining. Advances in Knowledge Discovery and Data Mining. 1996;375-397 AAAI/MIT Press, Cambridge, MA.
23. Fu Y., Han J. Metarule-guided mining of association rules in relational databases. Proceedings of the 1995 Internat. Workshop on Knowledge Discovery and Deductive and Object-Oriented Databases (KDOOD'95), Singapore. 1995;39-46.