Mining frequent patterns with multiple minimum supports using basic Apriori. - Tiantian Xu 002; Xiangjun Dong 001 (ICNC, 2013)

Select actionable positive or negative sequential patterns. - Xiangjun Dong 001; Chuanlu Liu; Tiantian Xu 002; Dakui Wang (J. Intell. Fuzzy Syst., 2015)

HUNSPM: An efficient algorithm for mining high utility negative sequential patterns. - Tongxuan Li; Tiantian Xu 002; Xiangjun Dong 001 (ICNC-FSKD, 2017)

e-NSPFI: Efficient Mining Negative Sequential Pattern from Both Frequent and Infrequent Positive Sequential Patterns. - Yongshun Gong; Tiantian Xu 002; Xiangjun Dong 001; Guohua Lv (Int. J. Pattern Recognit. Artif. Intell., 2017)

Mining High Utility Sequential Patterns with Negative Item Values. - Tiantian Xu 002; Xiangjun Dong 001; Jianliang Xu; Xue Dong (Int. J. Pattern Recognit. Artif. Intell., 2017)

E-msNSP: Efficient Negative Sequential Patterns Mining Based on Multiple Minimum Supports. - Tiantian Xu 002; Xiangjun Dong 001; Jianliang Xu; Yongshun Gong (Int. J. Pattern Recognit. Artif. Intell., 2017)

Application of Negative and Positive Association Rules in Mental Health Analysis of College Students. - Feng Hao 002; Long Zhao 002; Tiantian Xu 002; Xiangjun Dong 001 (ICNC-FSKD, 2018)

Efficient High Utility Negative Sequential Patterns Mining in Smart Campus. - Tiantian Xu 002; Tongxuan Li; Xiangjun Dong 001 (IEEE Access, 2018)

Rapid and Efficient Bug Assignment Using ELM for IOT Software. - Ying Yin; Xiangjun Dong 001; Tiantian Xu 002 (IEEE Access, 2018)

Erratum: "Mining High Utility Sequential Patterns with Negative Item Values". - Tiantian Xu 002; Xiangjun Dong 001; Jianliang Xu; Xue Dong (Int. J. Pattern Recognit. Artif. Intell., 2018)

Mining High Utility Sequential Patterns Using Multiple Minimum Utility. - Tiantian Xu 002; Jianliang Xu; Xiangjun Dong 001 (Int. J. Pattern Recognit. Artif. Intell., 2018)

An Efficient Algorithm to Mine High Average-Utility Sequential Patterns. - Tiantian Xu 002 (ICNC-FSKD, 2019)

Campus Data Analysis Based on Positive and Negative Sequential Patterns. - Xiaoqi Jiang; Tiantian Xu 002; Xiangjun Dong 001 (Int. J. Pattern Recognit. Artif. Intell., 2019)

Mining Top- ${k}$ Useful Negative Sequential Patterns via Learning. - Xiangjun Dong 001; Ping Qiu; Jinhu Lü; Longbing Cao; Tiantian Xu 002 (IEEE Trans. Neural Networks Learn. Syst., 2019)

A Structure-Induced Framework for Multi-Label Feature Selection With Highly Incomplete Labels. - Tiantian Xu 002; Long Zhao 002 (IEEE Access, 2020)

An efficient method for pruning redundant negative and positive association rules. - Xiangjun Dong 001; Feng Hao 002; Long Zhao 002; Tiantian Xu 002 (Neurocomputing, 2020)

e-HUNSR: An Efficient Algorithm for Mining High Utility Negative Sequential Rules. - Mengjiao Zhang; Tiantian Xu 002; Zhao Li; Xiqing Han; Xiangjun Dong 001 (Symmetry, 2020)

Mining Negative Sequential Rules from Negative Sequential Patterns. - Chuanhou Sun; Xiaoqi Jiang; Xiangjun Dong 001; Tiantian Xu 002; Long Zhao 002; Zhao Li; Yuhai Zhao (DASFAA (1), 2022)

Classifying the multi-omics data of gastric cancer using a deep feature selection method. - Yanyu Hu; Long Zhao 002; Zhao Li; Xiangjun Dong 001; Tiantian Xu 002; Yuhai Zhao (Expert Syst. Appl., 2022)

A random grouping-based self-regulating artificial bee colony algorithm for interactive feature detection. - Boxin Guan; Tiantian Xu 002; Yuhai Zhao; Yuan Li; Xiangjun Dong 001 (Knowl. Based Syst., 2022)

Toward Better Structure and Constraint to Mine Negative Sequential Patterns. - Xinming Gao; Yongshun Gong; Tiantian Xu 002; Jinhu Lü; Yuhai Zhao; Xiangjun Dong 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Learning Accurate Label-Specific Features From Partially Multilabeled Data. - Tiantian Xu 002; Yuanyuan Xu 002; Shiyu Yang; Binghao Li; Wenjie Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)