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Bay Vo
Publications
- 2021
- [j105]Tram Nguyen, Toan Bui, Hamido Fujita, Tzung-Pei Hong, Ho Dac Loc, Václav Snásel, Bay Vo:
Multiple-objective optimization applied in extracting multiple-choice tests. Eng. Appl. Artif. Intell. 105: 104439 (2021) - [j93]Quang-Thinh Bui, Bay Vo, Václav Snásel, Witold Pedrycz, Tzung-Pei Hong, Ngoc Thanh Nguyen, Mu-Yen Chen:
SFCM: A Fuzzy Clustering Algorithm of Extracting the Shape Information of Data. IEEE Trans. Fuzzy Syst. 29(1): 75-89 (2021) - 2020
- [j90]Bay Vo, Loan T. T. Nguyen, Nguyen Bui, Trinh D. D. Nguyen, Van-Nam Huynh, Tzung-Pei Hong:
An Efficient Method for Mining Closed Potential High-Utility Itemsets. IEEE Access 8: 31813-31822 (2020) - [j87]Bay Vo, Le V. Nguyen, Vinh V. Vu, Mi T. H. Lam, Thuy T. M. Duong, Ly T. Manh, Thuy T. T. Nguyen, Loan T. T. Nguyen, Tzung-Pei Hong:
Mining Correlated High Utility Itemsets in One Phase. IEEE Access 8: 90465-90477 (2020) - [j85]Thi-Thiet Pham, Tung Do, Anh Nguyen, Bay Vo, Tzung-Pei Hong:
An Efficient Method for Mining Top-K Closed Sequential Patterns. IEEE Access 8: 118156-118163 (2020) - [j77]Huy Minh Huynh, Loan T. T. Nguyen, Bay Vo, Unil Yun, Zuzana Komínková Oplatková, Tzung-Pei Hong:
Efficient algorithms for mining clickstream patterns using pseudo-IDLists. Future Gener. Comput. Syst. 107: 18-30 (2020) - [j71]Thang Mai, Loan T. T. Nguyen, Bay Vo, Unil Yun, Tzung-Pei Hong:
Efficient Algorithm for Mining Non-Redundant High-Utility Association Rules. Sensors 20(4): 1078 (2020) - [j70]Toan Bui, Tram Nguyen, Huy Minh Huynh, Bay Vo, Jerry Chun-Wei Lin, Tzung-Pei Hong:
Multiswarm Multiobjective Particle Swarm Optimization with Simulated Annealing for Extracting Multiple Tests. Sci. Program. 2020: 7081653:1-7081653:15 (2020) - 2019
- [c48]Huy Minh Huynh, Loan T. T. Nguyen, Bay Vo, Zuzana Komínková Oplatková, Tzung-Pei Hong:
Mining Clickstream Patterns Using IDLists. SMC 2019: 2007-2012 - 2018
- [j56]Huong Bui, Bay Vo, Ham Nguyen, Tu-Anh Nguyen-Hoang, Tzung-Pei Hong:
A weighted N-list-based method for mining frequent weighted itemsets. Expert Syst. Appl. 96: 388-405 (2018) - 2017
- [j52]Bay Vo, Tuong Le, Giang Nguyen, Tzung-Pei Hong:
Efficient Algorithms for Mining Erasable Closed Patterns From Product Datasets. IEEE Access 5: 3111-3120 (2017) - [j49]Jerry Chun-Wei Lin, Shifeng Ren, Philippe Fournier-Viger, Tzung-Pei Hong, Ja-Hwung Su, Bay Vo:
A fast algorithm for mining high average-utility itemsets. Appl. Intell. 47(2): 331-346 (2017) - [c43]Tzung-Pei Hong, Lu-Hung Chen, Shyue-Liang Wang, Chun-Wei Lin, Bay Vo:
Quasi-erasable itemset mining. IEEE BigData 2017: 1816-1820 - [c40]Tzung-Pei Hong, Kun-Yi Lin, Chun-Wei Lin, Bay Vo:
An incremental mining algorithm for erasable itemsets. INISTA 2017: 286-289 - 2016
- [j38]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) - [j35]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) - [j34]Bay Vo, Tam Tran, Tzung-Pei Hong, Le Minh Nguyen:
Using Soft Set Theory for Mining Maximal Association Rules in Text Data. J. Univers. Comput. Sci. 22(6): 802-821 (2016) - [j32]Bay Vo, Tuong Le, Frans Coenen, Tzung-Pei Hong:
Mining frequent itemsets using the N-list and subsume concepts. Int. J. Mach. Learn. Cybern. 7(2): 253-265 (2016) - 2015
- [j27]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) - [j22]Loan T. T. Nguyen, Bay Vo, Tzung-Pei Hong:
CARIM: an efficient algorithm for mining class-association rules with interestingness measures. Int. Arab J. Inf. Technol. 12(6A): 627-634 (2015) - [j20]Dang Nguyen, Loan T. T. Nguyen, Bay Vo, Tzung-Pei Hong:
A novel method for constrained class association rule mining. Inf. Sci. 320: 107-125 (2015) - [c30]Duy Ham Nguyen, Bay Vo, Thi Hong, Minh Nguyen, Tzung-Pei Hong:
An Improved Algorithm for Mining Frequent Weighted Itemsets. SMC 2015: 2579-2584 - 2014
- [j19]Bay Vo, Tuong Le, Tzung-Pei Hong, Hoai Bac Le:
An effective approach for maintenance of pre-large-based frequent-itemset lattice in incremental mining. Appl. Intell. 41(3): 759-775 (2014) - [j18]Thien-Phuong Le, Bay Vo, Tzung-Pei Hong, Bac Le, Dosam Hwang:
Improving Efficiency of Incremental Mining by Trie Structure and Pre-Large Itemsets. Comput. Informatics 33(3): 609-632 (2014) - [j15]Thi-Thiet Pham, Jiawei Luo, Tzung-Pei Hong, Bay Vo:
An efficient method for mining non-redundant sequential rules using attributed prefix-trees. Eng. Appl. Artif. Intell. 32: 88-99 (2014) - [j12]Tzung-Pei Hong, Yan-Liang Liou, Shyue-Liang Wang, Bay Vo:
Feature selection and replacement by clustering attributes. Vietnam. J. Comput. Sci. 1(1): 47-55 (2014) - [c28]Tien Lu, Bay Vo, Hien T. Nguyen, Tzung-Pei Hong:
A New Method for Mining High Average Utility Itemsets. CISIM 2014: 33-42 - 2013
- [j8]Loan T. T. Nguyen, Bay Vo, Tzung-Pei Hong, Hoang Chi Thanh:
CAR-Miner: An efficient algorithm for mining class-association rules. Expert Syst. Appl. 40(6): 2305-2311 (2013) - [j6]Bay Vo, Tzung-Pei Hong, Bac Le:
A lattice-based approach for mining most generalization association rules. Knowl. Based Syst. 45: 20-30 (2013) - [c24]Bac Le, Chanh-Truc Tran, Tzung-Pei Hong, Bay Vo:
A Space-Time Trade Off for FUFP-trees Maintenance. ACIIDS (2) 2013: 206-214 - [c22]Bay Vo, Chun-Wei Lin, Tzung-Pei Hong, Vinh V. Vu, Minh Nguyen, Bac Le:
An Efficient Method for Hiding High Utility Itemsets. KES-AMSTA 2013: 356-363 - [c21]Bay Vo, Tuong Le, Tzung-Pei Hong, Bac Le:
Maintenance of a Frequent-Itemset Lattice Based on Pre-large Concept. KSE (2) 2013: 295-305 - [c18]Bay Vo, Frans Coenen, Tuong Le, Tzung-Pei Hong:
A Hybrid Approach for Mining Frequent Itemsets. SMC 2013: 4647-4651 - [p4]Thien-Phuong Le, Bay Vo, Tzung-Pei Hong, Bac Le, Jason J. Jung:
Maintenance of IT-Tree for Transactions Deletion. Advanced Methods for Computational Collective Intelligence 2013: 157-166 - 2012
- [j5]Bay Vo, Tzung-Pei Hong, Bac Le:
DBV-Miner: A Dynamic Bit-Vector approach for fast mining frequent closed itemsets. Expert Syst. Appl. 39(8): 7196-7206 (2012) - [j4]Loan T. T. Nguyen, Bay Vo, Tzung-Pei Hong, Hoang Chi Thanh:
Classification based on association rules: A lattice-based approach. Expert Syst. Appl. 39(13): 11357-11366 (2012) - [c17]Loan T. T. Nguyen, Bay Vo, Tzung-Pei Hong, Hoang Chi Thanh:
A fast algorithm for classification based on association rules. GrC 2012: 365-369 - [c16]Chanh-Truc Tran, Bay Vo, Tzung-Pei Hong, Chun-Wei Lin, Bac Le:
An Enhanced FUFP-Tree Maintenance Approach for Transaction Deletion. IBICA 2012: 45-50 - [c15]Bay Vo, Minh-Thai Tran, Tzung-Pei Hong, Hieu Nguyen, Bac Le:
A Dynamic Bit-vector Approach for Efficiently Mining Inter-sequence Patterns. IBICA 2012: 51-56 - [c12]Loan T. T. Nguyen, Bay Vo, Tzung-Pei Hong, Hoang Chi Thanh:
Interestingness Measures for Classification Based on Association Rules. ICCCI (2) 2012: 383-392 - [c11]Thi-Thiet Pham, Jiawei Luo, Tzung-Pei Hong, Bay Vo:
MSGPs: A Novel Algorithm for Mining Sequential Generator Patterns. ICCCI (2) 2012: 393-401 - [c10]Thien-Phuong Le, Tzung-Pei Hong, Bay Vo, Bac Le:
An Efficient Incremental Mining Approach Based on IT-Tree. RIVF 2012: 1-5 - [c9]Bac Le, Thien-Phuong Le, Bay Vo, Tzung-Pei Hong:
Maintenance of DBV-Trees for Transaction Insertion. TAAI 2012: 165-170 - 2011
- [c6]Thien-Phuong Le, Bay Vo, Tzung-Pei Hong, Bac Le:
Incremental mining frequent itemsets based on the trie structure and the pre-large itemsets. GrC 2011: 369-373
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