Irreducible Frequent Patterns in Transactional Databases
Gennady P. Berman, Vyacheslav N. Gorshkov, Xidi Wang
Abstract
Irreducible frequent patters (IFPs) are introduced for transactional databases. An IFP is such a frequent pattern (FP),(x1,x2,...xn), the probability of which, P(x1,x2,...xn), cannot be represented as a product of the probabilities of two (or more) other FPs of the smaller lengths. We have developed an algorithm for searching IFPs in transactional databases. We argue that IFPs represent useful tools for characterizing the transactional databases and may have important applications to bio-systems including the immune systems and for improving vaccination strategies. The effectiveness of the IFPs approach has been illustrated in application to a classification problem.
Create a lesson
Related papers
Product Structure Meets Track Layouts
Michael A. Bekos, Giordano Da Lozzo, Petr Hliněný et al.
The Randomized Query Complexity of Finding Minimal Elements in Bounded-Width Posets
Luyao Fan, Jiayang Zou, Jiayang Gao et al.
On the Instance Optimality of Bidirectional Dijkstra's Algorithm
Matic Požar
Hadamard Flattening and Gaussian Pooling Sketch for Least Squares with Coordinate-wise Guarantee
Zhao Song, Lichen Zhang
Cheaper by the Batch: Shared Traversal for Genotype Graph Editing
Aaron Li, Yifan Li, Drew DeHaas et al.
Unpublished Draft: A Post-Processing Approach to Fairness in Tie-Aware Rankings
Somya Nigam, Johan Springael, Kenneth Sörensen