An Improved Apriori Algorithm Based on an Evolution-Communication Tissue-Like P System with Promoters and Inhibitors
An Improved Apriori Algorithm Based on an Evolution-Communication Tissue-Like P System with Promoters and Inhibitors
复制标题
基于具有启动子和抑制子的进化通讯类组织P系统的改进Apriori算法
DOI：
10.1155/2017/6978146
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发表时间：
2017-01-01
影响因子：
1.4
通讯作者：
Sun, Minghe
中科院分区：
文献类型：
--
作者：
Liu, Xiyu;Zhao, Yuzhen;Sun, Minghe
Apriori算法作为一种典型的频繁项集挖掘方法，可以帮助研究者和实践者从大量数据中发现隐含的关联。在这项工作中，一个快速的Apriori算法，称为ECTPPI-Apriori，用于处理大数据集，这是基于一个进化通信类组织P系统的启动子和抑制剂。ECTPPI-Apriori算法的结构是类组织的，算法的进化规则是对象重写规则。ECTPPI-Apriori算法的时间复杂度比传统的Apriori算法有了很大的改进。这些结果为利用膜计算模型改进传统算法提供了一些启示。
Apriori algorithm, as a typical frequent itemsets mining method, can help researchers and practitioners discover implicit associations from large amounts of data. In this work, a fast Apriori algorithm, called ECTPPI-Apriori, for processing large datasets, is proposed, which is based on an evolution-communication tissue-like P system with promoters and inhibitors. The structure of the ECTPPI-Apriori algorithm is tissue-like and the evolution rules of the algorithm are object rewriting rules. The time complexity of ECTPPI-Apriori is substantially improved from that of the conventional Apriori algorithms. The results give some hints to improve conventional algorithms by using membrane computing models.