A new method for mining disjunctive emerging patterns in high-dimensional datasets using hypergraphs
作者：
Highlights：
• Disjunctive emerging patterns can be found via minimal transversals in hypergraphs.
• We propose a new algorithm suitable for parallel and distributed environments.
• Experiments show that our method is efficient in terms of memory usage and computing time.
• We identified the key-features of datasets that affect most of our method.
摘要
Highlights•Disjunctive emerging patterns can be found via minimal transversals in hypergraphs.•We propose a new algorithm suitable for parallel and distributed environments.•Experiments show that our method is efficient in terms of memory usage and computing time.•We identified the key-features of datasets that affect most of our method.
论文关键词：Emerging patterns,Contrast pattern mining,Associative classifier,Minimal transversals,Hypergraphs,Microarray data
论文评审过程：Received 18 July 2013, Revised 17 September 2013, Accepted 18 September 2013, Available online 2 October 2013.
论文官网地址：https://doi.org/10.1016/j.is.2013.09.001
