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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Luna, J.M. Romero, J.R. Ventura, S. |
| Copyright Year | 2010 |
| Description | Author affiliation: Dept. of Computer Science and Numerical Analysis, University of Co´rdoba, Rabanales Campus, Albert Einstein building, 14071 Co´rdoba, Spain (Luna, J.M.; Romero, J.R.; Ventura, S.) |
| Abstract | This paper presents the G3PARM algorithm for mining representative association rules. G3PARM is an evolutionary algorithm that uses G3P (Grammar Guided Genetic Programming) and an auxiliary population made up of its best individuals who will then act as parents for the next generation. Due to the nature of G3P, the G3PARM algorithm allows us to obtain valid individuals by defining them through a context-free grammar and, furthermore, this algorithm is generic with respect to data type. We compare our algorithm to two multiobjective algorithms frequently used in literature and known as NSGA2 (Non dominated Sort Genetic Algorithm) and SPEA2 (Strength Pareto Evolutionary Algorithm) and demonstrate the efficiency of our algorithm in terms of running-time, coverage and average support, providing the user with high representative rules. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 194898 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424469093 |
| e-ISBN | 9781424469116 |
| DOI | 10.1109/CEC.2010.5586504 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-07-18 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Grammar Association rules Databases Evolutionary computation Genetic programming Encoding |
| Content Type | Text |
| Resource Type | Article |
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