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B-mine: Frequent Pattern Mining and Its Application to Knowledge Discovery from Social Networks

机译:B矿:频繁模式挖掘及其在社交网络知识发现中的应用

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As an important data mining task, frequent pattern mining has drawn attention from many researchers. This has led to the development of many frequent pattern mining algorithms, which include Apriori-based, tree-based, and hyperlinked array structure-based algorithms, as well as vertical mining algorithms. Although these algorithms are efficient and popular, they also suffer from some drawbacks. To tackle these drawbacks, we present in this paper an alternative algorithm called B-mine that uses a bitwise approach to mine frequent patterns. Evaluation results show the space- and time-efficiency of B-mine for frequent pattern mining, as well as the practicality of B-mine for social network analysis and knowledge discovery from social networks.
机译:作为重要的数据挖掘任务,频繁的模式挖掘已引起许多研究人员的关注。这导致了许多频繁模式挖掘算法的开发,包括基于Apriori,基于树和基于超链接数组结构的算法以及垂直挖掘算法。尽管这些算法是有效且流行的,但它们也存在一些缺点。为了解决这些缺点,我们在本文中提出了一种称为B-mine的替代算法,该算法使用按位方法来挖掘频繁模式。评估结果表明,B矿用于频繁模式挖掘的时空效率,以及B矿在社交网络分析和从社交网络中发现知识的实用性。

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