Tiantian Xu

Orcid: 0000-0001-6715-0351

Affiliations:
  • Qilu University of Technology, School of Information, Jinan, China
  • Shandong Academy of Sciences, China
  • Ocean University, Department of Software Engineering, China (PhD 2018)


According to our database1, Tiantian Xu authored at least 22 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Learning Accurate Label-Specific Features From Partially Multilabeled Data.
IEEE Trans. Neural Networks Learn. Syst., August, 2024

2023
Toward Better Structure and Constraint to Mine Negative Sequential Patterns.
IEEE Trans. Neural Networks Learn. Syst., February, 2023

2022
A random grouping-based self-regulating artificial bee colony algorithm for interactive feature detection.
Knowl. Based Syst., 2022

Classifying the multi-omics data of gastric cancer using a deep feature selection method.
Expert Syst. Appl., 2022

Mining Negative Sequential Rules from Negative Sequential Patterns.
Proceedings of the Database Systems for Advanced Applications, 2022

2020
e-HUNSR: An Efficient Algorithm for Mining High Utility Negative Sequential Rules.
Symmetry, 2020

An efficient method for pruning redundant negative and positive association rules.
Neurocomputing, 2020

A Structure-Induced Framework for Multi-Label Feature Selection With Highly Incomplete Labels.
IEEE Access, 2020

2019
Mining Top- ${k}$ Useful Negative Sequential Patterns via Learning.
IEEE Trans. Neural Networks Learn. Syst., 2019

Campus Data Analysis Based on Positive and Negative Sequential Patterns.
Int. J. Pattern Recognit. Artif. Intell., 2019

An Efficient Algorithm to Mine High Average-Utility Sequential Patterns.
Proceedings of the Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery - Proceedings of the 15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2019), Kunming, China, July 20-22, 2019, 2019

2018
Mining High Utility Sequential Patterns Using Multiple Minimum Utility.
Int. J. Pattern Recognit. Artif. Intell., 2018

Erratum: "Mining High Utility Sequential Patterns with Negative Item Values".
Int. J. Pattern Recognit. Artif. Intell., 2018

Rapid and Efficient Bug Assignment Using ELM for IOT Software.
IEEE Access, 2018

Efficient High Utility Negative Sequential Patterns Mining in Smart Campus.
IEEE Access, 2018

Application of Negative and Positive Association Rules in Mental Health Analysis of College Students.
Proceedings of the 14th International Conference on Natural Computation, 2018

2017
E-msNSP: Efficient Negative Sequential Patterns Mining Based on Multiple Minimum Supports.
Int. J. Pattern Recognit. Artif. Intell., 2017

Mining High Utility Sequential Patterns with Negative Item Values.
Int. J. Pattern Recognit. Artif. Intell., 2017

e-NSPFI: Efficient Mining Negative Sequential Pattern from Both Frequent and Infrequent Positive Sequential Patterns.
Int. J. Pattern Recognit. Artif. Intell., 2017

HUNSPM: An efficient algorithm for mining high utility negative sequential patterns.
Proceedings of the 13th International Conference on Natural Computation, 2017

2015
Select actionable positive or negative sequential patterns.
J. Intell. Fuzzy Syst., 2015

2013
Mining frequent patterns with multiple minimum supports using basic Apriori.
Proceedings of the Ninth International Conference on Natural Computation, 2013


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