Towards a logic query language for data mining

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

Volumn 2682, Issue , 2004, Pages 76-94

  Giannotti, Fosca ^a   Manco, Giuseppe ^b   Turini, Franco ^c  

^a CNR   (Italy)

^b ICAR CNR   (Italy)

^c UNIVERSITY OF PISA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 35048872666     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-44497-8_4     Document Type: Article

References (25)

1. J-F. Boulicaut, M. Klemettinen, and H. Mannila. Querying Inductive Databases: A Case Study on the MINE RULE Operator. In Procs. 2nd European Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD98), LNCS 1510, pages 194-202, 1998.
2. M.S. Chen, J. Han, and P.S. Yu. Data Mining: An Overview from a Database Perspective. IEEE Trans. on Knowledge and Data Engineering, 8(6):866-883,1996.
3. J. Dougherty, R. Kohavi, and M. Sahami. Supervised and Unsupervised Discretization of Continuous Features. In Procs. 12th International Conference on Machine Learning, pages 194-202, 1995.
4. F. Giannotti and G. Manco. Declarative knowledge extraction with iterative user-defined aggregates. AI*IA Notizie, 13(4), December 2000.
5. F. Giannotti and G. Manco. Making Knowledge Extraction and Reasoning Closer. In Procs. 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000), LNAI 1805, pages 360-371, 2000.
6. F. Giannotti, G. Manco, M. Nanni, and D. Pedreschi. Nondeterministic, Non-monotonic Logic Databases. IEEE Trans. on Knowledge and Data Engineering, 13(5):813-823, 2001.
7. F. Giannotti, G. Manco, D. Pedreschi, and F. Turini. Experiences with a Logic-Based Knowledge Discovery Support Environment. In Selected Papers of the Sixth congress of the Italian Congress of Artificial Intellingence, LNCS 1792, 2000.
8. F. Giannotti, G. Manco, and F. Turini. Specifying Mining Algorithms with Iterative User-Defined Aggregates: A Case Study. In Procs. 5th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2001), LNAI 2168, pages 128-139, 2001.
9. F. Giannotti, D. Pedreschi, and C. Zaniolo. Semantics and Expressive Power of Non Deterministic Constructs for Deductive Databases. Journal of Computer and Systems Sciences, 62(1):15-42, 2001.
10. G. Graefe, U. Fayyad, and S. Chaudhuri. On the Efficient Gathering of Sufficient Statistics for Classification from Large SQL Databases. In Proc. 4th Int. Conf. on Knowledge Discovery and Data Mining (KDD98), pages 204-208, 1998.
11. J. Han, Y. Fu, K. Koperski, W. Wang, and O. Zaiane. DMQL: A Data Mining Query Language for Relational Databases. In SIGMOD'96 Workshop on Research Issues on Data Mining and Knowledge Discovery (DMKD'96), 1996.
12. F. Hussain, H. Liu, C. Tan, and M. Dash. Discretization: An Enabling Technique. Journal of Knowledge Discovery and Data Mining, 6(4):393-423, 2002.
13. T. Imielinski and H. Mannila. A Database Perspective on Knowledge Discovery. Communications of the ACM, 39(11):58-64, 1996.
14. T. Imielinski and A. Virmani. MSQL: A Query Language for Database Mining. Journal of Knowledge Discovery and Data Mining, 3(4):373-408, 1999.
15. R. Kerber. ChiMerge: Discretization of Numeric Attributes. In Proc. 10th National Conference on Artificial Intelligence (AAAI92), pages 123-127. The MIT Press, 1992.
16. G. Manco. Foundations of a Logic-Based Framework for Intelligent Data Analysis. PhD thesis, Department of Computer Science, University of Pisa, April 2001.
17. H. Mannila. Inductive databases and condensed representations for data mining. In International Logic Programming Symposium, pages 21-30, 1997.
18. H. Mannila and H. Toivonen. Levelwise Search and Border of Theories in Knowledge Discovery. Journal of Knowledge Discovery and Data Mining, 3:241-258, 1997.
19. R. Meo, G. Psaila, and S. Ceri. A Tightly-Coupled Architecture for Data Mining. In International Conference on Data Engineering (ICDE98), pages 316-323,1998.
20. L. De Raedt. Data mining as constraint logic programming. In Procs. Int. Conf. on Inductive Logic Programming, 2000.
21. W. Shen, K. Ong, B. Mitbander, and C. Zaniolo. Metaqueries for Data Mining. In Advances in Knowledge Discovery and Data Mining, pages 375-398. AAAI Press/The MIT Press, 1996.
22. D. Tsur et al. Query Flocks: A Generalization of Association-Rule Mining. In Proc. ACM Conf. on Management of Data (Sigmod98), pages 1-12, 1998.
23. C. Zaniolo, N. Ami, and K. Ong. Negation and Aggregates in Recursive Rules: The LDL++ Approach. In Proc. 3rd Int. Conf. on Deductive and Object-Oriented Databases (DOOD93), LNCS 760, 1993.
24. C. Zaniolo, S. Ceri, C. Faloutsos, R.T Snodgrass, V.S. Subrahmanian, and R. Zicari. Advanced Database Systems. Morgan Kaufman, 1997.
25. C. Zaniolo and H. Wang. Logic-Based User-Defined Aggregates for the Next Generation of Database Systems. In The Logic Programming Paradigm: Current Trends and Future Directions, Springer Verlag, 1998.