Affiliation:
1. Military Medical Academy, The Russian Federation, Russia
Abstract
An analytical survey of some efficient current approaches to mining all kind of logical rules is presented including implicative and functional dependencies, association and classification rules. The interconnection between these approaches is analyzed. It is demonstrated that all the approaches are equivalent with respect to using the same key concepts of frequent itemsets (maximally redundant or closed itemset, generator, non-redundant or minimal generator, classification test) and the same procedures of their lattice structure construction. The main current tendencies in developing these approaches are considered.
Reference102 articles.
1. Towards long pattern generation in dense databases. In ACM;C.Aggarwal;SIGKDD Explorations,2001
2. Agrawal, R., Imielinski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. In Proceedings of the ACM-SIGMOD International Conference on Management of Data (SIGMOD’93), (pp. 207-216). Washington, DC.
3. Balcázar, J. L., & Tîrnăucă, C. (2011). Closed-Set-based discovery of representative association rules revisited. In A. Khenchaf & P. Poncelet (Eds.), Extraction et Gestion des Connaissances (EGC '11), Revue des Nouvelles Technologies de l'Information RNTI E.20 (Sous la direction de Djamel A. Zighed et Gilles Venturini), (pp. 635-646). Paris, France: Hermann, Éditeurs des sciences et des arts. ISBN 978 27056 8112 8
4. FILTERING ASSOCIATION RULES WITH NEGATIONS ON THE BASIS OF THEIR CONFIDENCE BOOST
5. Bastide, Y., Pasquier, N., Taouil, R., Stumme, G., & Lakhal, L. (2000). Mining minimal non- redundant association rules using frequent closed itemsets. In J. W. Lloyd, V. Dahl, U. Furbach, M. Kerber, K.-K. Lau, C. Palamidessi, L. M. Pereira, Y. Sagiv, & P. J. Stuckey (Eds.), Computational Logic (CL-2000), First International Conference, LNCS 1861 (pp. 972-986). Springer. ISBN 3-540-67797-6