Mining Positive and Negative Sequential Patterns in a Progressive Database

論文翻譯標題: 漸進式資料庫中正向與負向循序性樣式之探勘
  • 吳 永斌

學生論文: Master's Thesis


Positive sequential pattern (PSP) mining focuses on appearing items while negative sequential pattern (NSP) mining tends to find the relationship between occurring and non-occurring items There are few works involved in NSP mining and the definitions of NSP are inconsistent in each work The support threshold for PSP is always applied on NSP which cannot bring out interesting patterns In addition PSP has been discovered on incremental databases and progressive databases while NSP mining is only performed on static databases Progressive sequential pattern mining finds the most up-to-date patterns which can provide more valuable information However the previous progressive sequential pattern mining algorithm contains some redundant process In this paper we aim to find NSP on progressive databases A new definition of NSP is given to discover more meaningful and interesting patterns We propose an algorithm Propone for efficient mining process We also propose a lever-order traversal strategy and a pruning strategy to reduce the calculation time and the number of negative sequential candidates (NSC) By comparing Propone with some modified previous algorithms the experimental results show that Propone outperforms comparative algorithms
獎項日期2016 6月 29
監督員Jen-Wei Huang (Supervisor)