Superset Generation on Decision Diagrams
Generating all supersets from a given set family is important, because it is closely related to identifying cause-effect relationship. This paper presents an efficient method for superset generation by using the compressed data structures BDDs and ZDDs effectively. We analyze the size of a BDD that represents all supersets. As a by-product, we obtain a non-trivial upper bound for the size of a BDD that represents a monotone Boolean function in a fixed variable ordering.
Keywordssuperset binary decision diagram zero-suppressed binary decision diagram cause-effect relationship Boolean completion
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- 3.Kovalerchuk, B., Vityaev, E., Triantaphyllou, E.: How can AI procedures become more effective for manufacturings? In: Proc. of the Artificial Intelligence and Manufacturing Research Planning Workshop, Albuquerque, New, Mexico, pp. 103–111 (June 1996)Google Scholar
- 4.Judson, D.: Statistical rule induction in the presence of prior information: The bayesian record linkage problem. In: Triantaphyllou, E., Felici, G. (eds.) Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques. Massive Computing, vol. 6, pp. 655–694. Springer US (2006)Google Scholar
- 5.Knuth, D.E.: The Art of Computer Programming Volume 4a. Addison-Wesley Professional, New Jersey (2011)Google Scholar