Tai Dinh

According to our database, Tai Dinh authored at least 32 papers between 2015 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Exploring Urban Land Use Patterns by Pattern Mining and Unsupervised Learning.

Zdena Dobesová, Tai Dinh, Pavel Novák

CoRR, April, 2026

Ontology-driven personalized information retrieval for XML documents.

Ounnaci Iddir, Ahmed-Ouamer Rachid, Tai Dinh

CoRR, March, 2026

Silhouette-upper-bound: An upper bound on the silhouette evaluation metric for clustering.

Hugo Sträng, Tai Dinh

Softw. Impacts, 2026

An upper bound on the silhouette evaluation metric for clustering.

Hugo Sträng, Tai Dinh

Pattern Recognit., 2026

2025

Reinforcement Learning from Probabilistic Forecasts for Safe Decision-Making via Conditional Value-at-Risk Planning.

Michal Koren, Or Peretz, Tai Dinh, Philip S. Yu

CoRR, October, 2025

An upper bound of the silhouette validation metric for clustering.

Hugo Sträng, Tai Dinh

CoRR, September, 2025

Estimating the Optimal Number of Clusters in Categorical Data Clustering by Silhouette Coefficient.

Duy-Tai Dinh, Tsutomu Fujinami, Van-Nam Huynh

CoRR, January, 2025

Categorical data clustering: 25 years beyond K-modes.

Tai Dinh, Wong Hauchi, Philippe Fournier-Viger, Daniil Lisik, Minh-Quyet Ha, Hieu-Chi Dam, Van-Nam Huynh

Expert Syst. Appl., 2025

An efficient fusion-based deep learning framework for land use and land cover image clustering.

Tai Dinh, Dat Tran, Zdena Dobesová, Huynh Van Hong, Daniil Lisik, Rameesh Khan

Eng. Appl. Artif. Intell., 2025

A Mixed-Methods Framework for Analyzing Travel Reviews with LLMs and MAXQDA: A Case Study in Osaka.

Daud Santoso, Tai Dinh, Shehan Liyanaarachchi, Wuyi Yue

Proceedings of the Model and Data Engineering - 14th International Conference, 2025

Sentiment Analysis of Travel Reviews in Kyoto Using LLMs.

Shehan Liyanaarachchi, Tai Dinh, Wuyi Yue, Trung Vo, Le-Minh Nguyen

Proceedings of the Advanced Data Mining and Applications - 21st International Conference, 2025

2024

Data clustering: an essential technique in data science.

Wong Hauchi, Daniil Lisik, Tai Dinh

CoRR, 2024

Enhanced Feature-Based Clustering for Urban Land Use Pattern Detection.

Rameesh Khan, Zdena Dobesová, Yang Yu, Tai Dinh

Proceedings of the 16th International Conference on Knowledge and System Engineering, 2024

2023

A method for k-means-like clustering of categorical data.

Thu-Hien Thi Nguyen, Duy-Tai Dinh, Songsak Sriboonchitta, Van-Nam Huynh

J. Ambient Intell. Humaniz. Comput., 2023

Mining compact high utility sequential patterns.

Tai Dinh, Philippe Fournier-Viger, Huynh Van Hong

CoRR, 2023

Mining Insights From Esports Game Reviews With an Aspect-Based Sentiment Analysis Framework.

Yang Yu, Duy-Tai Dinh, Ba-Hung Nguyen, Fangyu Yu, Van-Nam Huynh

IEEE Access, 2023

Understanding Mobile Game Reviews Through Sentiment Analysis: A Case Study of PUBGm.

Yang Yu, Tai Dinh, Fangyu Yu, Van-Nam Huynh

Proceedings of the Model and Data Engineering - 12th International Conference, 2023

2022

Multi-core parallel algorithms for hiding high-utility sequential patterns.

Ut Huynh, Bac Le, Duy-Tai Dinh, Hamido Fujita

Knowl. Based Syst., 2022

2021

Clustering mixed numerical and categorical data with missing values.

Duy-Tai Dinh, Van-Nam Huynh, Songsak Sriboonchitta

Inf. Sci., 2021

2020

Combining Correlation-Based Feature and Machine Learning for Sensory Evaluation of Saigon Beer.

Nhat-Vinh Lu, Trong-Nhan Vuong, Duy-Tai Dinh

Int. J. Knowl. Syst. Sci., 2020

Mining correlated high-utility itemsets using various measures.

Philippe Fournier-Viger, Yimin Zhang, Jerry Chun-Wei Lin, Duy-Tai Dinh, Hoai Bac Le

Log. J. IGPL, 2020

k-PbC: an improved cluster center initialization for categorical data clustering.

Duy-Tai Dinh, Van-Nam Huynh

Appl. Intell., 2020

2018

An efficient algorithm for Hiding High Utility Sequential Patterns.

Bac Le, Duy-Tai Dinh, Van-Nam Huynh, Quang-Minh Nguyen, Philippe Fournier-Viger

Int. J. Approx. Reason., 2018

A pure array structure and parallel strategy for high-utility sequential pattern mining.

Bac Le, Ut Huynh, Duy-Tai Dinh

Expert Syst. Appl., 2018

An efficient algorithm for mining periodic high-utility sequential patterns.

Duy-Tai Dinh, Bac Le, Philippe Fournier-Viger, Van-Nam Huynh

Appl. Intell., 2018

A New Context-Based Clustering Framework for Categorical Data.

Thanh-Phu Nguyen, Duy-Tai Dinh, Van-Nam Huynh

Proceedings of the PRICAI 2018: Trends in Artificial Intelligence, 2018

k-CCM: A Center-Based Algorithm for Clustering Categorical Data with Missing Values.

Duy-Tai Dinh, Van-Nam Huynh

Proceedings of the Modeling Decisions for Artificial Intelligence, 2018

2017

Mining Periodic High Utility Sequential Patterns.

Tai Dinh, Van-Nam Huynh, Bac Le

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.

Minh Nguyen Quang, Tai Dinh, Ut Huynh, Bac Le

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.

Minh Nguyen Quang, Ut Huynh, Tai Dinh, Nghia Hoai Le, Bac Le

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2016

Mining Correlated High-Utility Itemsets Using the Bond Measure.

Philippe Fournier-Viger, Jerry Chun-Wei Lin, Tai Dinh, Hoai Bac Le

Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

2015

A Novel Approach for Hiding High Utility Sequential Patterns.

Tai Dinh, Minh Nguyen Quang, Bac Le

Proceedings of the Sixth International Symposium on Information and Communication Technology, 2015