Abstract
As an important data mining technique, implication rules help to explore the dependencies among attributes of a database. In this paper, we aim at finding an efficient algorithm to discover the implication rules in a data set. This algorithm first extends the concept lattice theory by building the lattice according to the data set with the interesting attributes to improve user interaction and mining efficiency. The interesting concept lattice, together with the rough set theory, is then incorporated into our method to implement a new interesting rough lattice-based implication rules discovery (IRLIRD) approach to interactively acquire the rules with the specific rough upper and lower approximation. It generates implication rules without multiple passes over the data set and computing frequent itemsets. For the application of the proposed method to the transaction data set of the large-scale supermarkets, a novel data structure, which is based on the numeric attribute and termed as linked list of transaction set, is introduced here to reduce the needed memory. A simulation is implemented to illustrate the whole mining process, which demonstrates that the approach reduces the computational time greatly comparing with that of the classical Apriori algorithm. The algorithm can also be extended to many other application areas such as stock analysis, credit card distribution and agricultural application, etc.
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References
Pawlak Z. Rough Sets. Kluwer Academic Publishers, Dordrecht, 1991.
Ziarko W. Variable precision rough set model. Journal of Computer and System Scientifics 46, 1993, 39–59.
Njiwoua P., Nguifo E.M. IGLUE: an instance-based learning system over lattice theory. In Proceedings of International Conference on Tools with Artificial Intelligence, Newport Beach, California, 1997: 75–76.
Njiwoua P., Nguifo E.M. A parallel algorithm to build concept lattice. In Proceedings of 4th Groningen International Information Technique Conference for students, 1997: 103–107.
Frawley W.J., Shapiro GP., et al. Knowledge discovery in databases: an overview. In Shapiro G.P. and Frawley W.J., editors, Knowledge Discovery in Databases. AAAI/MIT, Cambridge, MA, 1991: 1–27.
Missaoui R., Godin R. Search for concepts and dependencies in databases. International Workshop on Rough Sets and Knowledge Discovery, Banff, Alberta, Springer-Verlag. 1994: 17–23.
Agrawal R, Mannila H, Srikant R et al. Fast Discovery of Association Rules. In: Fayyad M, Piatetsky-Shapiro G, Smyth P Eds. Advances in Knowledge Discovery and Data Mining, Menlo Park, AAAI Press, 1996: 307–328.
Hu X, Cercone N. Mining Knowledge Rules from Databases: A Rough Set Approach. In: Proceedings of the 12th International Conference on Data Engineering, New Orleans, Louiseana, 1996: 96–105.
Wille R. Concept lattice & Conceptual knowledge system. Computer Mathematics Applied, 23 (6–9), 1992: 493–515.
Pawlak Z., Ziarko W. Rough Sets. Communication of the ACM, 38 (11), Nov. 1995: 36–41.
Oosthuizen G.D. Rough sets and concept lattices. In Proceedings of International Conference on Rough Sets and Knowledge Discovery, Bannf, 1993.
Wu X. Induction as pre-processing. In Proceedings of 3`d PAKDD-99, Beijing, China, Springer, 1999: 114–122.
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© 2001 Physica-Verlag Heidelberg
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Zhao, Y., Shi, J., Ruan, D., Shi, P. (2001). Interesting Rough Lattice-based Implication Rules Discovery. In: Ruan, D., Kacprzyk, J., Fedrizzi, M. (eds) Soft Computing for Risk Evaluation and Management. Studies in Fuzziness and Soft Computing, vol 76. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1814-7_7
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DOI: https://doi.org/10.1007/978-3-7908-1814-7_7
Publisher Name: Physica, Heidelberg
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