1 citations · 2 across the 6 of their papers we have counts for
6 papers
Maximal co-occurrence nonoverlapping sequential rule mining
Yan Li, Chang Zhang, Jie Li +4
The aim of sequential pattern mining (SPM) is to discover potentially useful information from a given se-quence. Although various SPM methods have been investigated, most of these…
Nonoverlapping (delta, gamma)-approximate pattern matching
Youxi Wu, Bojing Jian, Yan Li +2
Pattern matching can be used to calculate the support of patterns, and is a key issue in sequential pattern mining (or sequence pattern mining). Nonoverlapping pattern matching mea…
OPR-Miner: Order-preserving rule mining for time series
Youxi Wu, Xiaoqian Zhao, Yan Li +4
Discovering frequent trends in time series is a critical task in data mining. Recently, order-preserving matching was proposed to find all occurrences of a pattern in a time series…
Deep Forest with Hashing Screening and Window Screening
Pengfei Ma, Youxi Wu, Yan Li +4
As a novel deep learning model, gcForest has been widely used in various applications. However, the current multi-grained scanning of gcForest produces many redundant feature vecto…
One-off Negative Sequential Pattern Mining
Youxi Wu, Mingjie Chen, Yan Li +4
Negative sequential pattern mining (SPM) is an important SPM research topic. Unlike positive SPM, negative SPM can discover events that should have occurred but have not occurred,…
OPP-Miner: Order-preserving sequential pattern mining
Youxi Wu, Qian Hu, Yan Li +3
A time series is a collection of measurements in chronological order. Discovering patterns from time series is useful in many domains, such as stock analysis, disease detection, an…