Tai Dinh

Orcid: 0000-0001-7597-4262

According to our database1, Tai Dinh authored at least 19 papers between 2015 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Bibliography

2023
A method for k-means-like clustering of categorical data.
J. Ambient Intell. Humaniz. Comput., 2023

Mining compact high utility sequential patterns.
CoRR, 2023

Mining Insights From Esports Game Reviews With an Aspect-Based Sentiment Analysis Framework.
IEEE Access, 2023

Understanding Mobile Game Reviews Through Sentiment Analysis: A Case Study of PUBGm.
Proceedings of the Model and Data Engineering - 12th International Conference, 2023

2022
Multi-core parallel algorithms for hiding high-utility sequential patterns.
Knowl. Based Syst., 2022

2021
Clustering mixed numerical and categorical data with missing values.
Inf. Sci., 2021

2020
Combining Correlation-Based Feature and Machine Learning for Sensory Evaluation of Saigon Beer.
Int. J. Knowl. Syst. Sci., 2020

Mining correlated high-utility itemsets using various measures.
Log. J. IGPL, 2020

k-PbC: an improved cluster center initialization for categorical data clustering.
Appl. Intell., 2020

2018
An efficient algorithm for Hiding High Utility Sequential Patterns.
Int. J. Approx. Reason., 2018

A pure array structure and parallel strategy for high-utility sequential pattern mining.
Expert Syst. Appl., 2018

An efficient algorithm for mining periodic high-utility sequential patterns.
Appl. Intell., 2018

A New Context-Based Clustering Framework for Categorical Data.
Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

k-CCM: A Center-Based Algorithm for Clustering Categorical Data with Missing Values.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2018

2017
Mining Periodic High Utility Sequential Patterns.
Proceedings of the Intelligent Information and Database Systems - 9th Asian Conference, 2017

2016
MHHUSP: An integrated algorithm for mining and Hiding High Utility Sequential Patterns.
Proceedings of the 2016 Eighth International Conference on Knowledge and Systems Engineering, 2016

An Approach to Decrease Execution Time and Difference for Hiding High Utility Sequential Patterns.
Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2016

Mining Correlated High-Utility Itemsets Using the Bond Measure.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

2015
A Novel Approach for Hiding High Utility Sequential Patterns.
Proceedings of the Sixth International Symposium on Information and Communication Technology, 2015


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