基于列表结构的加权可擦除项集挖掘算法

可擦除项集挖掘是从大规模产品数据库中挖掘出低利润项集，以解决厂商财务危机的方法。传统挖掘方法只处理静态产品数据库，在提取可擦除项集时忽略项本身的权值。为解决现有可擦除项集挖掘算法考虑条件单一、效率低下的问题，提出一种有效的在增量数据集上挖掘加权可擦除项集的算法WELI。该算法综合考虑了数据不断积累和项具有不同重要性的因素，采用简洁的列表结构减少内存消耗，利用权重条件进行项集修剪，并结合包含索引和差集思想简化增益的计算过程，以实现高效的增量挖掘操作。实验表明：就运行时间和内存消耗而言，该算法在稠密数据集和稀疏数据集上均具有良好的实验效果，就可伸缩性而言，该算法也优于以往算法。

A weighted erasable itemset mining algorithm based on list structure

Erasable itemset mining is an approach of mining low profit itemset from large-scale pro- duct databases in order to solve the financial crisis of manufactures. Traditional erasable itemset mining methods deal with static product databases only, and ignore the weight of item itself when they extract the erasable itemset. To address the problem of single condition and the inefficiency of existing erasable itemset mining algorithms, an effective algorithm WELI is proposed to mine erasable itemset in an incremental database with weighted condition. The proposed algorithm comprehensively considers the factors of data accumulation and different importance of items. The concise list structure is applied to reduce the memory consumption. Besides, the proposed algorithm prunes the invalid itemset with the weight conditions. Whats more, it can simplify the process of gain calculation by combining subsume index and difference set. Therefore, it can achieve incremental mining operations efficiently. Experiments show that, in terms of running time and memory consumption, the algorithm has good experimental results on both dense and sparse data sets. In terms of scalability, the algorithm is also superior to previous algorithms.