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Pro./Dr. LE HOAI BAC

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Email: lhbac@fit.hcmus.edu.vn


Position Held
  • 09/2018 - present: Head of Computer Science Department, Faculty of Information Technology, University of Science, VNU-HCM.
  • 2003 - 07/2018: Vice Dean, Head of department, Faculty of Information Technology, University of Science, VNU-HCM
Courses Taught
  • Fundamentals of Artificial Intelligence
  • Data Mining and Applications
  • Knowledge-based Systems
Research Interests
  • Artificial Intelligence
  • Data Mining
  • Data Science
  • Machine Learning
Selected Publication
  • Tin C. Truong, Hai V. Duong, Bac Le, Philippe Fournier-Viger: Efficient Vertical Mining of High Average-Utility Itemsets Based on Novel Upper-Bounds. IEEE Trans. Knowl. Data Eng. 31(2): 301-314 (2019)
  • Linh Nguyen, Giang Nguyen, Bac Le: Fast algorithms for mining maximal erasable patterns. Expert Syst. Appl. 124: 5066 (2019)
  • 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)
  • Bac Le, Phuc Luong. Optimized cardinality-based generalized itemset mining using transaction ID and numeric encoding. Applied. Intelligence. 48(8): 2067-2080 (2018)
  • Trang Van, Atsuo Yoshitaka, Bac Le. Mining web access patterns with super-pattern constraint. Applied. Intelligence. 48(11): 3902-3914 (2018)
  • Hai V. Duong, Tin C. Truong, Bac Le. Efficient algorithms for simultaneously mining concise representations of sequential patterns based on extended pruning conditions. Eng. Appl. of AI 67: 197-210 (2018)
  • 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)
  • 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. Reasoning 95: 77-92 (2018)
  • Thien-Trang Van, Bay Vo, Bac Le. Mining sequential patterns with itemset constraints. Knowl. Inf. Syst. 57(2): 311-330 (2018)
  • Tung Kieu, Bay Vo, Tuong Le, Zhi-Hong Deng, Bac Le. Mining top-k co-occurrence items with sequential pattern. Expert Syst. Appl. 85: 123-133 (2017)
  • Bac Le, Hai V. Duong, Tin C. Truong, Philippe FournierViger. FCloSM, FGenSM: two efficient algorithms for mining frequent closed and generator sequences using the local pruning strategy. Knowl. Inf. Syst. 53(1): 71-107 (2017)
  • Anh Tran, Tin C. Truong, Bac Le. Efficiently mining association rules based on maximum single constraints. Vietnam J. Computer Science 4(4): 261-277 (2017)
  • Philippe Fournier-Viger, Jerry Chun-Wei Lin, Bay Vo, Tin Chi Truong, Ji Zhang, Hoai Bac Le. A survey of itemset mining. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 7(4) (2017)
  • Minh-Thai Tran, Bac Le, Bay Vo, Tzung-Pei Hong. Mining non-redundant sequential rules with dynamic bit vectors and pruning techniques. Appl. Intell. 45(2): 333-342 (2016)
  • Bay Vo, Thien-Phuong Le, Tzung-Pei Hong, Bac Le, Jason J. Jung. An efficient approach for mining frequent item sets with transaction deletion operation. Int. Arab J. Inf. Technol. 13(5): 595-602 (2016
  • Hoai Bac Le, Minh-Thai Tran, Bay Vo. Mining frequent closed inter-sequence patterns efficiently using dynamic bit vectors. Appl. Intell. 43(1): 74-84 (2015)
  • Giang Nguyen, Tuong Le, Bay Vo, Hoai Bac Le. EIFDD: An efficient approach for erasable itemset mining of very dense datasets. Appl. Intell. 43(1): 85-94 (2015)
  • Bay Vo, Tuong Le, Tzung-Pei Hong, Hoai Bac Le. Fast updated frequent-itemset lattice for transaction deletion. Data Knowl. Eng. 96: 78-89 (2015)
  • Dang Nguyen, Bay Vo, Bac Le. CCAR: An efficient method for mining class association rules with itemset constraints. Eng. Appl. of AI 37: 115-124 (2015)
  • Minh-Thai Tran, Bac Le, Bay Vo. Combination of dynamic bit vectors and transaction information for mining frequent closed sequences efficiently. Eng. Appl. of AI 38: 183-189 (2015)
  • Quyen Huynh-Thi-Le, Tuong Le, Bay Vo, Hoai Bac Le. An efficient and effective algorithm for mining top-rank-k frequent patterns. Expert Syst. Appl. 42(1): 156-164 (2015)
  • Huan Phan, Bac Le: A Novel Algorithm for Frequent Itemsets Mining in Transactional Databases. PAKDD (Workshops) 2018: 243-255
  • Tuan-Anh D. Le, Duc-Tan Lam, Phong Vo, Atsuo Yoshitaka, Hoai Bac Le:Recover Water Bodies in Multi-spectral Satellite Images with Deep Neural Nets. SoICT 2018: 281-288
  • Long Mai, Bac Le. Aspect-Based Sentiment Analysis of Vietnamese Texts with Deep Learning. ACIIDS (1) 2018: 149158
  • Huan Phan, Bac Le. Novel Parallel Algorithm for Frequent Itemsets Mining in Large Transactional Databases. ICDM 2018: 272-287
  • Tin Truong, Anh Tran, Hai Duong, Bac Le and Philippe Fournier-Viger. EHUSM: Mining High Utility Sequences with a Pessimistic Utility Model. UDM-August 20, 2018, London, United Kingdom.
  • Bac Le, Minh-Thai Tran, Duy Tran. A Method for Early Pruning a Branch of Candidates in the Process of Mining Sequential Patterns. ACIIDS (1) 2017: 487
  • Tai Dinh, Van-Nam Huynh, Bac Le. Mining Periodic High Utility Sequential Patterns. ACIIDS (1) 2017: 545-555
  • Nghia Pham Trong, Hung Nguyen, Kazunori Kotani, Hoai Bac Le. A Comprehensive Survey on Human Activity Prediction. ICCSA (1) 2017: 411-425
  • Hung Thanh Vu, Khoa Pho, Bac Le. Flexible 3D neighborhood cascade deformable part models for object detection. ICIP 2017: 910-914
  • Khoa Pho, Hung Vu, Bac Le. Adaptive cascade threshold learning from negative samples for deformable part models. ICIP 2017: 1547-1551
  • Tho Hoang, Bac Le, Minh-Thai Tran. Distributed algorithm for sequential pattern mining on a large sequence dataset. KSE 2017: 18-23
  • Quan-Hoang Vo, Huy-Tien Nguyen, Bac Le, Minh-Le Nguyen. Multi-channel LSTM-CNN model for Vietnamese sentiment analysis. KSE 2017: 24-29
  • Khue Doan, Minh Nguyen Quang, Bac Le. Applied Cuckoo Algorithm for Association Rule Hiding Problem. SoICT 2017: 26-33
  • 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
  • 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
  • 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
  • Giang Nguyen, Tuong Le, Bay Vo, Bac Le. Discovering Erasable Closed Patterns. ACIIDS (1) 2015: 368-376
  • Bac Le, Huy Nguyen. Twitter Sentiment Analysis Using Machine Learning Techniques. ICCSAMA 2015: 279-289
  • Hung Thanh Vu, Mai Vuong Minh Nhat, Bac Le. An Efficient Model for Simultaneous Face Detection, Pose Estimation and Landmark Localisation. KSE 2015: 13-18
  • Tai Dinh, Minh Nguyen Quang, Bac Le. A Novel Approach for Hiding High Utility Sequential Patterns. SoICT 2015: 121-128
  • Selected Domestic Publications
  • Lê Hoài Bắc, Nguyễn Thị Quyên. Khai thác k mẫu tuần tự tối đại sử dụng cây dữ liệu chiếu tiền tố. Tạp chí Công nghệ thông tin và Truyền thông. Chuyên san: Các công trình NC, PT và UD CNTT – TT. Tập V-1. Số 15(35). 06/2016. Pp 76-85
  • Nguyen Vinh Nam, Le Hoai Bac. "A visual framework for Spatial Data mining". Journal Information Technologies & Communications, Vol E-3, 8(12) 2015. Trang 67 – 72
  • Lê Hoài Bắc, Phan Thành Huấn. "Thuật toán hiệu quả khai thác tập phổ biến tối đại trên cơ sở dữ liệu giao dịch lớn". FAIR'9 – 2016. Kỷ yếu Hội nghị Khoa học Quốc gia lần thứ IX - Nghiên cứu cơ bản và ứng dụng Công nghệ thông tin; Trang 721 – 728
  • Minh-Thai Tran, Bay Vo, Bac Le, Tzung-Pei Hong. "An Approach for mining Non – Redundant sequential Rules Efficiencly". NICS – 2015. 2nd national foundation for Science and Technology development conference on Information and Computer Scicen. 277 – 282
  • Hai Duong, Tin Truong, Bac Le. An Efficient Parallel Algorithm for Mining Both Frequent Closed and Generator Sequences on Multi-core Processors. 2018 5th NAFOSTED Conference on Information and Computer Science (NICS)