ディン・ズイ・タイ

Dinh Duy Tai
ディン・ズイ・タイ

経歴

  • MSc in Information Systems, US-VNUHCM.
  • 北陸先端科学技術大学院大学博士後期課程修了，博士（知識科学）
  • 北陸先端科学技術大学院大学研究員

メッセージ

Quantitative, Qualitative, and Mixed Methods Research

私の研究哲学は主に定量的手法に根ざしており，探索的データ分析，統計モデリング，機械学習などのツールを用いて，パターンの発見，仮説の検証，一般化可能な洞察の生成を行っています。構造化されたデータ主導の分析を重視する一方で，複雑な問題や人間中心の問題に取り組む場合は特に，定性的手法や混合的手法も大切にしています。この柔軟で実践的なアプローチにより，私は多様な方法論を活用して研究結果を充実させ，検証することができるのです。

このような考え方から，学生にはダイナミックで成長著しいデータサイエンスの分野を探求するよう勧めています。データサイエンス専門分野では，データ分析，プログラミング，機械学習などの実践的なスキルを身につけることができます。ビジネス，ヘルスケア，テクノロジー，社会科学のいずれに興味があろうとも，この学びは幅広いキャリアと研究の機会への扉を開くものです。KCGIで，このエキサイティングな分野でのあなたの旅をサポートできることを楽しみにしています。

担当科目

  • Exploratory Data Analysis and Visualization
  • Theories of Data Mining
  • Qualitative Data: Analysis and Transformation
  • Data Analysis
  • Object Oriented System Design
  • Fundamentals of Database Technology

専門分野

  • Data science
  • Data mining
  • Machine learning

業績

Refereed journals

  • Tai Dinh, Wong Hauchi, Daniil Lisik, Michal Koren, Dat Tran, S.Yu Philip, Joaquín Torres- Sospedra. Data clustering: an essential technique in data science and management. Data Science and Management, 2025.
  • 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. Expert Systems with Applications 272, 126608, 2025.
  • Daniil Lisik, Rani Basna, Tai Dinh, Christian Hennig, Syed Ahmar Shah, G¨oran Wennergren, Emma Goks¨or, Bright I Nwaru. Artificial intelligence in pediatric allergy research. European journal of pediatrics, pages 1-20, 2025.
  • Thu-Hien Thi Nguyen, Duy-Tai Dinh, Songsak Sriboonchitta, and Van-Nam Huynh. A method for k-means-like clustering of categorical data. Journal of Ambient Intelligence and Humanized Computing, volume 14, number 11, pages 15011-15021, 2023.
  • 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, volume 11, pages 61161 - 61172, 2023.
  • Hirosuke Matsui, Yuta Muramoto, Takashi Kakubo, Naoya Amino, Tomoya Uruga, MinhQuyet Ha, Duy-Tai Dinh, Hieu-Chi Dam, and Mizuki Tada. Machine-learning-revealed reaction statistics via 3D spectroimaging for copper sulfidation of adhesive layers in rubber/brass composite. Communications Materials (Nature) 4, 88, 2023.
  • Tai Dinh, Philippe Fournier-Viger, Huynh Van Hong. Mining compact high utility sequential Patterns. Nippon(Japan) Applied Informatics Society, volume 17, pages 45-57, 2023.
  • Duy-Tai Dinh, Van-Nam Huynh, and Songsak Sriboonchitta. Clustering mixed numeric and categorical data with missing values. Information Sciences, volume 571, pages 418-442, 2021.
  • Ut Huynh, Bac Le, Duy-Tai Dinh, Hamido Fujita. Multi-core parallel algorithms for hiding high-utility sequential patterns. Knowledge-based systems, pages 107793, 2021.
  • Duy-Tai Dinh, and Van-Nam Huynh. k-PbC: An improved cluster center initialization for categorical data clustering. Applied Intelligence, volume 50, pages 2610–2632, 2020.
  • Nhat-Vinh Lu, Trong-Nhan Vuong, Duy-Tai Dinh. Combining correlation-based feature and machine learning for sensory evaluation of saigon beer. International Journal of Knowledge and Systems Science (IJKSS), pages 71-85, 2020.
  • Philippe Fournier-Viger, Jerry Chun-Wei Lin, Yimin Zhang, Duy-Tai Dinh, Hoai Bac Le. Mining correlated high-utility itemsets using various measures. Logic Journal of the IGPL, Oxford University Press, 2020.
  • Duy-Tai Dinh, Bac Le, Philippe Fournier-Viger, and Van-Nam Huynh. An effcient algorithm for mining periodic high-utility sequential patterns. Applied Intelligence, volume 48, pages 4694-4714, 2018.
  • Bac Le, Duy-Tai Dinh, Van-Nam Huynh, Quang-Minh Nguyen, and Philippe Fournier-Viger. An efficient algorithm for hiding high utility sequential patterns. International Journal of Approximate Reasoning, volume 95, pages 77-92, 2018.
  • Bac Le, Ut Huynh, and Duy-Tai Dinh. A pure array structure and parallel strategy for high-utility sequential pattern mining. Expert Systems with Applications, volume 104, pages 107-120, 2018.

International conferences

  • Rameesh Khan, Zdena Dobesova, Yu Yang, Tai Dinh. Enhanced Feature-based Clustering for Urban Land Use Pattern Detection. The 16th International Conference on Knowledge and Systems Engineering 2024, 5 – 7 November 2024, Kuala Lumpur, Malaysia.
  • Yang Yu, Duy-Tai Dinh, Fangyu Yu and Van-Nam Huynh. Understanding Mobile Game Reviews Through Sentiment Analysis: A Case Study of PUBGm. 12th International Conference on Model and Data Engineering (MEDI 2023), pages 102-115, Springer, 2023.
  • Yang Yu, Ba Hung Nguyen, Duy-Tai Dinh, Fangyu Yu, Tsutomu Fujinami, Van Nam Huynh. A Topic Modeling Approach for Exploring Attraction of Dark Souls Series Reviews on Steam. Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems, University of Venice, Venice, Italy, February 22-24, 2022.
  • Duy-Tai Dinh, Tsutomu Fujinami, and Van-Nam Huynh. Estimating the optimal number of clusters in categorical data clustering by silhouette coefficient. Twentieth International Symposium on Knowledge and Systems Sciences (KSS 2019), pages 1-17, Springer, 2019.
  • Duy-Tai Dinh, and Van-Nam Huynh. k-CCM: A center-based algorithm for clustering categorical data with missing values. Fifteenth International Conference on Modeling Decisions for Artificial Intelligence (MDAI 2018), pages 267-279, Springer, 2018.
  • Thanh-Phu Nguyen, Duy-Tai Dinh, and Van-Nam Huynh. A new context-based clustering framework for categorical data. Fifteenth Pacific Rim International Conference on Artificial Intelligence (PRICAI 2018), pages 697-709, Springer, 2018.
  • Duy-Tai Dinh, Van-Nam Huynh, and Bac Le. Mining periodic high utility sequential patterns. Ninth Asian Conference on Intelligent Information and Database Systems, pages 545-555, Springer, 2017.
  • Minh Nguyen Quang, Ut Huynh, Duy-Tai Dinh, Nghia Hoai Le and Bac Le. An Approach to Decrease Execution Time and Difference for Hiding High Utility Sequential Pattern. Fifth International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2016), pages 435-446, Springer, 2016.
  • Minh Nguyen Quang, Duy-Tai Dinh, Ut Huynh, Bac Le, MHHUSP. An integrated algorithm for mining and Hiding High Utility Sequential Patterns. Eighth International Conference on Knowledge and Systems Engineering (KSE 2016), pages 13-18, Springer, 2016.
  • Philippe Fournier-Viger, Jerry Chun-Wei Lin, Duy-Tai Dinh and Hoai Bac Le. Mining Correlated High-Utility Itemsets Using the Bond Measure. Eleventh International Conference on Hybrid Artificial Intelligence Systems (HAIS 2016), pages 53-65, Springer, 2016.
  • Duy-Tai Dinh, Minh Nguyen Quang, Bac Le. A Novel Approach for Hiding High Utility Sequential Patterns. Sixth International Symposium on Information and Communication Technology (SoICT 2015), pages 121-128, ACM, 2015.

Book chapters and posters

  • Duy-Tai Dinh, Van-Nam Huynh, Bac Le, Philippe Fournier-Viger, Ut Huynh, Quang-Minh Nguyen “A survey of privacy preserving utility mining”, High-Utility Pattern Mining, pages 207-232, Springer, 2019.
  • Ut Huynh, Duy-Tai Dinh, Bac Le, Van-Nam Huynh. Mining Periodic High-Utility Sequential Patterns with Negative Unit Profits. Periodic Pattern Mining: Theory, Algorithms and Applications, pages 153-170, Springer, 2021.
  • Ut Huynh, Duy-Tai Dinh, Bac Le. Hiding Periodic High-Utility Sequential Patterns. Periodic Pattern Mining: Theory, Algorithms and Applications, pages 171-189, Springer, 2021.
  • Philippe Fournier-Viger, Youxi Wu, Duy-Tai Dinh, Wei Song, Jerry Chun-Wei Lin. Discovering periodic high utility itemsets in a discrete sequence. Periodic Pattern Mining: Theory, Algorithms and Applications, pages 133-151, Springer, 2021.
  • Duy-Tai Dinh, Duong-Nguyen Nguyen, Hieu-Chi Dam. On the nature of mixed-type features in materials datasets. Pacifichem 2021: A Creative Vision for the Future, December 16-21, 2021, Virtual.