Resumen de ParaMiner: a generic pattern mining algorithm for multi-core architectures
Benjamin Negrevergne, Alexandre Termier, Marie-Christine Rousset, Jean-François Méhaut
In this paper, we present ParaMinerwhich is a genericand parallelalgorithm for closed pattern mining. ParaMineris built on the principles of pattern enumeration in strongly accessible set systems. Its efficiency is due to a novel dataset reductiontechnique (that we call EL-reduction), combined with novel technique for performing dataset reduction in a parallel execution on a multi-core architecture. We illustrate ParaMiner’s genericity by using this algorithm to solve three different pattern mining problems: the frequent itemset mining problem, the mining frequent connected relational graphs problem and the mining gradual itemsets problem. In this paper, we prove the soundness and the completeness of ParaMiner. Furthermore, our experiments show that despite being a generic algorithm, ParaMinercan compete with specialized state of the art algorithms designed for the pattern mining problems mentioned above. Besides, for the particular problem of gradual itemset mining, ParaMineroutperforms the state of the art algorithm by two orders of magnitude.
