Mining Top-k Distinguishing Periodic Patterns in Temporal Databases

摘要：

　　Distinguishing pattern mining,which is an important task in data mining,aims to find the differences between collections of data.However,the existing distinguishing pattern min-ing methods fail to consider the problem that some patterns appear regularly in one class of data sets and irregularly in another class,which may lose some interesting patterns.To fill this gap,we propose a new problem named mining top-k distinguishing periodic patterns in temporal databases.We aim to find k patterns with the most significant difference be-tween two classes of data sets with a period constraint.And we introduce an algorithm called kDPP-Miner to solve this problem.Several pruning rules are designed to improve its efficiency.The experimental results in real data sets demon-strate that our algorithm is effective and efficient.

关键词： temporal database distinguishing pattern periodic pattern

作者: Jie Liu Jie Zuo Ruiqi Qin

作者单位: Sichuan University Chengdu,China

会议类型: 国际会议

会议名称: 2019国图灵大会(ACM Turing Celebration conference-China 2019 )

会议地点: 成都

会议语种:英文

页码: 47-51

在线出版日期: 2019-05-17（万方平台首次上网日期，不代表论文的发表时间）