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20212023
most citedMaximal co-occurrence nonoverlapping sequential rule mining

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.DB2023

Repetitive nonoverlapping sequential pattern mining

Meng Geng, Youxi Wu, Yan Li +4

Sequential pattern mining (SPM) is an important branch of knowledge discovery that aims to mine frequent sub-sequences (patterns) in a sequential database. Various SPM methods have…

cs.LG2023

Sequential three-way decisions with a single hidden layer feedforward neural network

Youxi Wu, Shuhui Cheng, Yan Li +2

The three-way decisions strategy has been employed to construct network topology in a single hidden layer feedforward neural network (SFNN). However, this model has a general perfo…

cs.DB20231 cited

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…

cs.DB2022

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…

cs.LG2022

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…

cs.DB2022

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,…