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2020 – today
- 2024
[i2]Tai Dinh, Wong Hauchi, Philippe Fournier-Viger, Daniil Lisik, Minh-Quyet Ha, Hieu-Chi Dam, Van-Nam Huynh:
Categorical data clustering: 25 years beyond K-modes. CoRR abs/2408.17244 (2024)- 2023
- [j10]Yang Yu
, Duy-Tai Dinh, Ba-Hung Nguyen, Fangyu Yu, Van-Nam Huynh:
Mining Insights From Esports Game Reviews With an Aspect-Based Sentiment Analysis Framework. IEEE Access 11: 61161-61172 (2023) - [j9]Thu-Hien Thi Nguyen, Duy-Tai Dinh, Songsak Sriboonchitta, Van-Nam Huynh:
A method for k-means-like clustering of categorical data. J. Ambient Intell. Humaniz. Comput. 14(11): 15011-15021 (2023) - [c8]Yang Yu, Tai Dinh, Fangyu Yu, Van-Nam Huynh:
Understanding Mobile Game Reviews Through Sentiment Analysis: A Case Study of PUBGm. MEDI 2023: 102-115 - [i1]Tai Dinh, Philippe Fournier-Viger, Huynh Van Hong:
Mining compact high utility sequential patterns. CoRR abs/2302.11426 (2023) - 2022
- [j8]Ut Huynh, Bac Le, Duy-Tai Dinh, Hamido Fujita:
Multi-core parallel algorithms for hiding high-utility sequential patterns. Knowl. Based Syst. 237: 107793 (2022) - 2021
- [j7]Duy-Tai Dinh, Van-Nam Huynh, Songsak Sriboonchitta:
Clustering mixed numerical and categorical data with missing values. Inf. Sci. 571: 418-442 (2021) - 2020
- [j6]Duy-Tai Dinh, Van-Nam Huynh:
k-PbC: an improved cluster center initialization for categorical data clustering. Appl. Intell. 50(8): 2610-2632 (2020) - [j5]Philippe Fournier-Viger, Yimin Zhang, Jerry Chun-Wei Lin, Duy-Tai Dinh, Hoai Bac Le:
Mining correlated high-utility itemsets using various measures. Log. J. IGPL 28(1): 19-32 (2020) - [j4]Nhat-Vinh Lu, Trong-Nhan Vuong, Duy-Tai Dinh:
Combining Correlation-Based Feature and Machine Learning for Sensory Evaluation of Saigon Beer. Int. J. Knowl. Syst. Sci. 11(2): 71-85 (2020)
2010 – 2019
- 2018
- [j3]Duy-Tai Dinh, Bac Le, Philippe Fournier-Viger, Van-Nam Huynh:
An efficient algorithm for mining periodic high-utility sequential patterns. Appl. Intell. 48(12): 4694-4714 (2018) - [j2]Bac Le, Ut Huynh, Duy-Tai Dinh:
A pure array structure and parallel strategy for high-utility sequential pattern mining. Expert Syst. Appl. 104: 107-120 (2018) - [j1]Bac Le, Duy-Tai Dinh, Van-Nam Huynh, Quang-Minh Nguyen, Philippe Fournier-Viger:
An efficient algorithm for Hiding High Utility Sequential Patterns. Int. J. Approx. Reason. 95: 77-92 (2018) - [c7]Duy-Tai Dinh, Van-Nam Huynh:
k-CCM: A Center-Based Algorithm for Clustering Categorical Data with Missing Values. MDAI 2018: 267-279 - [c6]Thanh-Phu Nguyen, Duy-Tai Dinh, Van-Nam Huynh:
A New Context-Based Clustering Framework for Categorical Data. PRICAI (1) 2018: 697-709 - 2017
- [c5]Tai Dinh, Van-Nam Huynh, Bac Le:
Mining Periodic High Utility Sequential Patterns. ACIIDS (1) 2017: 545-555 - 2016
- [c4]Philippe Fournier-Viger, Jerry Chun-Wei Lin, Tai Dinh, Hoai Bac Le:
Mining Correlated High-Utility Itemsets Using the Bond Measure. HAIS 2016: 53-65 - [c3]Minh Nguyen Quang, Ut Huynh, Tai Dinh, Nghia Hoai Le, Bac Le:
An Approach to Decrease Execution Time and Difference for Hiding High Utility Sequential Patterns. IUKM 2016: 435-446 - [c2]Minh Nguyen Quang, Tai Dinh, Ut Huynh, Bac Le:
MHHUSP: An integrated algorithm for mining and Hiding High Utility Sequential Patterns. KSE 2016: 13-18 - 2015
- [c1]Tai Dinh, Minh Nguyen Quang, Bac Le:
A Novel Approach for Hiding High Utility Sequential Patterns. SoICT 2015: 121-128
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