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2020 – today
- 2024
[j13]Djeane Debora Onthoni
, Ming-Yen Lin, Kuei-Yuan Lan, Tsung-Hsien Huang, Hong-Ming Lin, Hung-Yi Chiou, Chih-Cheng Hsu, Ren-Hua Chung:
Latent space representation of electronic health records for clustering dialysis-associated kidney failure subtypes. Comput. Biol. Medicine 183: 109243 (2024)- [j12]Ming-Yen Lin, Ping-Chun Wu, Sue-Chen Hsueh:
Optimizing Session-Aware Recommenders: A Deep Dive into GRU-Based Latent Interaction Integration. Future Internet 16(2): 51 (2024) - [c27]Chih-Yuan Li, Jun-Ting Wu, Chan Hsu, Ming-Yen Lin, Yihuang Kang:
Understanding eGFR Trajectories and Kidney Function Decline via Large Multimodal Models. MIPR 2024: 667-673 - [i2]Chih-Yuan Li, Jun-Ting Wu, Chan Hsu, Ming-Yen Lin, Yihuang Kang:
Understanding eGFR Trajectories and Kidney Function Decline via Large Multimodal Models. CoRR abs/2409.02530 (2024) - 2023
- [j11]Hsing Paul Luh, Ming-Yen Lin, Ping-Hsun Wu:
A single framework of precision surveillance of diabetes disease prognosis for better care with collaboration. J. Integr. Des. Process. Sci. 27(1): 27-39 (2023) - [c26]Sue-Chen Hsueh, Min-Shan Shih, Ming-Yen Lin:
Context Enhanced Recurrent Neural Network for Session-Aware Recommendation. TAAI (2) 2023: 53-67 - 2022
- [j10]Ming-Yen Lin, Cheng-Tai Fu, Sue-Chen Hsueh:
Interactive Mining of Probabilistic Frequent Patterns in Uncertain Databases. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 30(2): 263-283 (2022) - [c25]Cheng-Ru Li, Chih-Chung Yang, Chun-Han Chou, Ming-Yen Lin, Yu-Hsuan Lin:
Quality Analysis and Colour Decoding of Printed Matters using a Portable 2D Chroma Meter. PHOTOPTICS 2022: 123-127 - 2021
- [j9]Ming-Yen Lin, Jia-Sin Liu, Tzu-Yang Huang, Ping-Hsun Wu, Yi-Wen Chiu, Yihuang Kang, Chih-Cheng Hsu, Shang-Jyh Hwang, Hsing Paul Luh:
Data Analysis of the Risks of Type 2 Diabetes Mellitus Complications before Death Using a Data-Driven Modelling Approach: Methodologies and Challenges in Prolonged Diseases. Inf. 12(8): 326 (2021) - [c24]Ming-Yen Lin, Yu-Ju Lin, Sue-Chen Hsueh:
Using Spark for Text Mining on Large Scale Liver Cancer Literature. BDET 2021: 82-87 - [c23]Yihuang Kang, Yi-Wen Chiu, Ming-Yen Lin, Fang-Yi Su, Sheng-Tai Huang:
Towards Model-informed Precision Dosing with Expert-in-the-loop Machine Learning. IRI 2021: 342-347 - [i1]Yihuang Kang, Yi-Wen Chiu, Ming-Yen Lin, Fang-Yi Su, Sheng-Tai Huang:
Towards Model-informed Precision Dosing with Expert-in-the-loop Machine Learning. CoRR abs/2106.14384 (2021) - 2020
- [c22]Cheng-Ru Li, Hsin-Yi Tsai, Chih-Chung Yang, Ming-Yen Lin, Kuo-Cheng Huang, Yu-Hsuan Lin:
Quantifying the color changes in bruised skin using a color-calibrated imaging system. MeMeA 2020: 1-5
2010 – 2019
- 2018
- [j8]Ming-Yen Lin, Sue-Chen Hsueh, Chih-Chen Chan:
Mining and Maintenance of Sequential Patterns using a Backward Generation Framework. J. Inf. Sci. Eng. 34(5): 1329-1349 (2018) - 2017
- [c21]Ming-Yen Lin, Yueh-Lin Lin, Sue-Chen Hsueh:
Discovering Group Skylines with Constraints by Early Candidate Pruning. ADMA 2017: 49-62 - 2016
- [c20]Chih-Yu Wang, Ming-Yen Lin:
Prediction of accrual expenses in balance sheet using decision trees and linear regression. TAAI 2016: 73-77 - 2015
- [c19]Ming-Yen Lin, Tien-Jing Wang, Sue-Chen Hsueh:
Improving MapReduce-based Entity-resolution by Data-load Balancing. ASE BD&SI 2015: 50:1-50:6 - 2014
- [c18]Chin-Wang Tao, Ming-Yen Lin, Chen-Chia Chuang, Tsu-Tian Lee, Chia-Wen Chang:
Design of a DSP-based biaxial solar tracking system. SCIS&ISIS 2014: 892-895 - 2013
- [c17]Ming-Yen Lin, Tsung-Che Li, Sue-Chen Hsueh:
Improving classification accuracy of associative classifiers by using k-conflict-rule preservation. ICUIMC 2013: 14 - 2012
- [j7]Ming-Yen Lin, Tzer-Fu Tu, Sue-Chen Hsueh:
High utility pattern mining using the maximal itemset property and lexicographic tree structures. Inf. Sci. 215: 1-14 (2012) - [c16]Ming-Yen Lin, Cheng-Tai Fu, Sue-Chen Hsueh:
Incremental update on probabilistic frequent itemsets in uncertain databases. ICUIMC 2012: 75:1-75:8 - [c15]Ming-Yen Lin, Pei-Yu Lee, Sue-Chen Hsueh:
Apriori-based frequent itemset mining algorithms on MapReduce. ICUIMC 2012: 76:1-76:8 - 2010
- [c14]Ming-Yen Lin, Sue-Chen Hsueh, Chien-Hsiang Tung:
Interactive stream mining of maximal frequent itemsets allowing flexible time intervals and support thresholds. ICUIMC 2010: 35
2000 – 2009
- 2009
- [c13]Ming-Yen Lin, Sue-Chen Hsueh, Chih-Chen Chan:
Incremental Discovery of Sequential Patterns Using a Backward Mining Approach. CSE (1) 2009: 64-70 - [c12]Ming-Yen Lin, Sue-Chen Hsueh, Ming-Hong Chen, Hong-Yang Hsu:
Mining Sequential Patterns for Image Classification in Ubiquitous Multimedia Systems. IIH-MSP 2009: 303-306 - [r1]Ming-Yen Lin:
Time-Constrained Sequential Pattern Mining. Encyclopedia of Data Warehousing and Mining 2009: 1974-1978 - 2008
- [j6]Ming-Yen Lin, Sue-Chen Hsueh, Chia-Wen Chang:
Fast discovery of sequential patterns in large databases using effective time-indexing. Inf. Sci. 178(22): 4228-4245 (2008) - [j5]Ming-Yen Lin, Sue-Chen Hsueh, Chia-Wen Chang:
Mining Closed Sequential Patterns with Time Constraints. J. Inf. Sci. Eng. 24(1): 33-46 (2008) - [c11]Ming-Yen Lin, Sue-Chen Hsueh, Sheng-Kun Hwang:
Interactive Mining of Frequent Itemsets over Arbitrary Time Intervals in a Data Stream. ADC 2008: 15-21 - [c10]Sue-Chen Hsueh, Ming-Yen Lin, Chien-Liang Chen:
Mining Negative Sequential Patterns for E-commerce Recommendations. APSCC 2008: 1213-1218 - [c9]Ming-Yen Lin, Sue-Chen Hsueh, Chung-Yi Wang:
Interactive Mining of Frequent Patterns in a Data Stream of Time-Fading Models. ISDA (1) 2008: 513-518 - 2007
- [c8]Sue-Chen Hsueh, Ming-Yen Lin, Kun-Lin Lu:
Mining Generalized Association Rules for Service Recommendations for Digital Home Applications. IIH-MSP 2007: 631-634 - 2006
- [c7]Ming-Yen Lin, Sue-Chen Hsueh, Chia-Wen Chang:
Fast Discovery of Time-Constrained Sequential Patterns Using Time-Indexes. ADMA 2006: 693-701 - [c6]Ming-Yen Lin, Sue-Chen Hsueh, Sheng-Kun Hwang:
Variable Support Mining of Frequent Itemsets over Data Streams Using Synopsis Vectors. PAKDD 2006: 724-728 - 2005
- [j4]Ming-Yen Lin, Suh-Yin Lee:
Fast Discovery of Sequential Patterns through Memory Indexing and Database Partitioning. J. Inf. Sci. Eng. 21(1): 109-128 (2005) - [j3]Ming-Yen Lin, Suh-Yin Lee:
Efficient mining of sequential patterns with time constraints by delimited pattern growth. Knowl. Inf. Syst. 7(4): 499-514 (2005) - 2004
- [j2]Ming-Yen Lin, Suh-Yin Lee:
Incremental update on sequential patterns in large databases by implicit merging and efficient counting. Inf. Syst. 29(5): 385-404 (2004) - [j1]Ming-Yen Lin, Suh-Yin Lee:
Interactive sequence discovery by incremental mining. Inf. Sci. 165(3-4): 187-205 (2004) - 2003
- [c5]Ming-Yen Lin, Suh-Yin Lee:
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery. HICSS 2003: 68 - 2002
- [c4]Ming-Yen Lin, Suh-Yin Lee:
Fast Discovery of Sequential Patterns by Memory Indexing. DaWaK 2002: 150-160 - [c3]Ming-Yen Lin, Suh-Yin Lee, Sheng-Shun Wang:
DELISP: Efficient Discovery of Generalized Sequential Patterns by Delimited Pattern-Growth Technology. PAKDD 2002: 198-209 - 2000
- [c2]Ming-Yen Lin, Suh-Yin Lee:
A Fast Lexicographic Algorithm for Association Rule Mining in Web Applications. ICDCS Workshop of Knowledge Discovery and Data Mining in the World-Wide Web 2000: F7-F14
1990 – 1999
- 1998
- [c1]Ming-Yen Lin, Suh-Yin Lee:
Incremental update on sequential patterns in large databases. ICTAI 1998: 24-31
Coauthor Index
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