Abstract
Inductive and deductive inference are both essential ingredients of scientific activity. This paper takes a database-centred view some of the crucial issues arising in any attempt to combine these two modes of inference. It explores how a recently-proposed class of database systems (that support the execution of composite tasks, each of whose steps may involve knowledge discovery, as an inductive process, and or query answering, as a deductive one) might deliver significant benefits in the context of a case study where the specific characteristics of such systems can be more vividly perceived as being relevant and nontrivial.
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References
Alpdemir, M., Mukherjee, A., Gounaris, A., Paton, N., Watson, P., Fernandes, A., Fitzgerald, D.: OGSA-DQP: Service-based distributed querying on the grid. In: Bertino, E., Christodoulakis, S., Plexousakis, D., Christophides, V., Koubarakis, M., Böhm, K., Ferrari, E. (eds.) EDBT 2004. LNCS, vol. 2992, pp. 858–861. Springer, Heidelberg (2004)
Aragão, M.A.T., Fernandes, A.A.A.: Characterizing web service substitutivity with combined deductive and inductive engines. In: Yakhno, T. (ed.) ADVIS 2002. LNCS, vol. 2457, pp. 244–254. Springer, Heidelberg (2002)
Aragão, M.A.T., Fernandes, A.A.A.: Inductive-deductive databases for knowledge management. In: Proc. ECAI KM&OM 2002, pp. 11–19 (2002)
Aragão, M.A.T., Fernandes, A.A.A.: A case study on seamless support for combined knowledge discovery and query answering (2003), Longer version of this, Available from http://www.cs.man.ac.uk/~alvaro/
Aragão, M.A.T., Fernandes, A.A.A.: Combining query answering and knowledge discovery. Technical report, University of Machester (2003), Available from http://www.cs.man.ac.uk/~alvaro/
Aragão, M.A.T., Fernandes, A.A.A.: Logic-based integration of query answering and knowledge discovery. In: Christiansen, H., Hacid, M.-S., Andreasen, T., Larsen, H.L. (eds.) FQAS 2004. LNCS (LNAI), vol. 3055, pp. 68–83. Springer, Heidelberg (2004)
Bergadano, F.: Inductive database relations. IEEE TKDE 5(6), 969–971 (1993)
Fegaras, L., Maier, D.: Optimizing object queries using an effective calculus. ACM TODS 25(4), 457–516 (2000)
Graefe, G.: Query evaluation techniques for large databases. ACM Computing Surveys 25(2), 73–170 (1993)
Han, J., Fu, Y., Wang, W., Chiang, J., Zaïane, O.R., Koperski, K.: DBMiner: interactive mining of multiple-level knowledge in relational databases. In: Proc. SIGMOD 1996, pp. 550–550s (1996)
Imielinski, T., Virmani, A.: MSQL: A query language for database mining. DMKD 3(4), 373–408 (1999)
Lakshmanan, L.V.S., Shiri-Varnaamkhaasti, N.: A parametric approach to deductive databases with uncertainty. IEEE TKDE 13(4), 554–570 (2001)
Lee, S.D., de Raedt, L.: An algebra for inductive query evaluation. In: Proc. ICDM 2003 (2003)
Mannila, H.: Inductive databases and condensed representations for data mining. In: Proc. ILP, vol. 13, pp. 21–30 (1997)
Meo, R., Psaila, G., Ceri, S.: A new SQL-like operator for mining association rules. In: Proc. VLDB 1996, pp. 122–133 (1996)
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Aragão, M.A.T., Fernandes, A.A.A. (2004). Seamlessly Supporting Combined Knowledge Discovery and Query Answering: A Case Study. In: Suzuki, E., Arikawa, S. (eds) Discovery Science. DS 2004. Lecture Notes in Computer Science(), vol 3245. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30214-8_37
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DOI: https://doi.org/10.1007/978-3-540-30214-8_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23357-2
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