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Wei-Chao Lin

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Wei-Chao Lin
Associate Professor
TEL: (03)2118800 # 3770
Email: viclin@gap.cgu.edu.tw
Education: Ph.D. in Information Systems, University of Sunderland, UK
Research interests: Data Mining, Big Data Analysis, Information Retrieval
Personal Web page

 



　Associate professor, Department of Information Management, Chang Gung University 2017/08 ~
　Executive Secretary, Center for Institutional Research, Chang Gung University 2021/02 ~
　Associate researcher, Department of Thoracic Surgery, Chang Gung Memorial Hospital at Linkou 2017/11 ~


　Associate researcher, Center for IR, Chang Gung University 2017/08~2021/01
　Associate professor, Department of CSIE, Asia University, 2016/02~2017/07
　Associate professor, Department of CSIE, HWH, 2015/07~2016/01
　Assistant professor, Department of CSIE, HWH, 2011/09~2015/06
　Vice Director, Department of CSIE, HWH, 2015/08~2016/01
　Section leader, AIS of CNC, HWH, 2012/02~2015/07
　Postdoc, Institute of Information Science, Academia Sinica, 2010/08~2011/09

 

 

Courses:
　Electronic Commerce
　Introduction to Computer Science
　Introduction to Internet of Things
　Big Data Analytical Methods
　Introduction to Intelligent Robotics
　Seminar on Information Technology and Applications

Projects:
　MOST Research Projects

  • Binary Decomposition Approaches in Multi-Class Datasets (MOST 110-2410-H-182-002-), Project Manager, 110/08/01~111/07/31
  • Multi-modal Deep Learning Architecture for Stock Price Prediction (MOST 109-2410-H-182-012-), Project Manager, 109/08/01~110/07/31
  • Machine Learning Based Data Sampling for Class-Imbalanced Datasets (MOST 106-2410-H-182-024-), Project Manager, 106/08/01~107/07/31
  • User-centred Interaction in Text-Based Image Retrieval (NSC 101-2218-E-146-001-), Project Manager, 101/08/01~102/07/31

Journal Papers:

  1. Lin, W.-C., Tsai, C.-F.*, and Zhong, J.R. (2022) Deep Learning for Missing Value Imputation of Continuous Data and the Effect of Data Discretization. Knowledge-Based Systems (SCI; IF=8.038; 16/139 Q1(2020-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) (accepted)
  2. Lin, W.-C.* (2021) Block-Based Pseudo-relevance Feedback for Image Retrieval. Journal of Experimental & Theoretical Artificial Intelligence (SCI; IF=2.340; 79/140 Q3(2020-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) (online first)
  3. Wang, Z., Tsai, C.-F., and Lin, W.-C.* (2021) Data Cleaning Issues in Class Imbalanced Datasets: Instance Selection and Missing Values Imputation for One-Class Classifiers.Data Technologies and Applications, 55(5), pp. 771-787. (SSCI; IF=1.667; 52/86 Q3(2020-JCR) in COMPUTER SCIENCE, INTERDISCIPLINARY APPLICTIONS)
  4. Wang, M.-C., Tsai, C.-F., and Lin, W.-C.* (2021) Towards Missing Electric Power Data Imputation for Energy Management Systems.Expert Systems With Applications, 174, 114743. (SCI; IF=6.954; 8/84 Q1(2020-JCR) in OPERATIONS RESEARCH & MANAGEMENT SCIENCE)
  5. Huang, M.-W., Tsai C.-F., and Lin, W.-C.* (2021) Instance Selection in Medical Datasets: A Divide-and-Conquer Framework. Computers & Electrical Engineering, 90, 106957. (SCI; IF=3.818; 44/112 Q2(2020-JCR) in COMPUTER SCIENCE, INTERDISCIPLINARY APPLICTIONS)
  6. Chen, C.-W., Tsai, Y.-H., Chang, F.-R., and Lin, W.-C.* (2020) Ensemble Feature Selection in Medical Datasets: Combining Filter, Wrapper, and Embedded Feature Selection Results. Expert Systems, Special Issue on Advances in Visual Analytics and Mining Visual Data, 37(5), e12553. (SCI; IF=2.587; 31/110 Q2(2020-JCR) in COMPUTER SCIENCE, THEORY & METHODS)
  7. Lin, W.-C. and Tsai, C.-F.* (2020) Missing Value Imputation: A Review and Analysis of the Literature (2006-17). Artificial Intelligence Review, 53(2), pp. 1487-1509. (SCI; IF= 8.139; 14/139 Q1(2020-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
  8. Tsai, C.-F., Lin, W.-C.*, Hu, Y.-H., and Yao, G.-T. (2019) Under-Sampling Class Imbalanced Datasets by Combining Clustering Analysis and Instance Selection. Information Sciences, 477, pp. 47-54. (SCI; IF=5.910; 9/156 Q1(2019-JCR) in COMPUTER SCIENCE, INFORMATION SYSTEMS)
  9. Lin, W.-C., Lu, Y.-H., and Tsai, C.-F.* (2019) Feature Selection in Single and Ensemble Learning Based Bankruptcy Prediction Models. Expert Systems, 36(1), e12335. (SCI; IF=1.546; 50/108 Q2(2019-JCR) in COMPUTER SCIENCE, THEORY & METHODS)
  10. Tsai, C.-F., Li, M.-L., and Lin, W.-C.*(2018) A Class Center Based Approach for Missing Value Imputation. Knowledge-Based Systems, 151, pp. 124-135. (SCI; IF=5.101; 17/134 Q1(2018-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
  11. Huang, M.-W.,Lin, W.-C.*, and Tsai, C.-F. (2018) Outlier Removal in Model-Based Missing Value Imputation for Medical Datasets. Journal of Healthcare Engineering, Special Issue on Artificial Intelligence in Medical Applications, 2018, Article ID 1817479. (SCI; IF=1.295; 79/98 Q4(2018-JCR) in HEALTH CARE SCIENCES & SERVICES)
  12. Lin, W.-C., Tsai, C.-F.*, Hu, Y.-H., and Jhang, J.-S. (2017) Clustering-Based Undersampling for Class-imbalanced Data. Information Sciences, 409-410, pp. 17-26. (SCI; IF=4.305; 12/148 Q1(2017-JCR) in COMPUTER SCIENCE, INFORMATION SYSTEMS)
  13. Lin, W.-C., Ke, S.-W., and Tsai, C.-F.* (2017) When Should We Ignore Examples with Missing Values? International Journal of Data Warehousing and Mining, 13(4), pp. 53-63. (SCI; IF=0.781; 86/104 Q4(2017-JCR) in COMPUTER SCIENCE, SOFTWARE ENGINEERING)
  14. Lin, W.-C., Ke, S.-W., and Tsai, C.-F.* (2017) Top 10 Data Mining Algorithms in Business Applications: A Brief Survey. Kybernetes, 46(7), pp.1158-1170. (SCI; IF=0.980; 16/22 Q3(2017-JCR) in COMPUTER SCIENCE, CYBERNETICS)
  15. Lin, W.-C.* (2017) On Image Search Result Aggregation. Pattern Analysis and Applications, 20(3), pp. 865-870. (SCI; IF=1.281; 86/132 Q3(2017-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
  16. Ke, S.-W., Lin, W.-C.*, Tsai, C.-F., and Hu, Y.-H. (2017) Soft Estimation by Hierarchical Classification and Regression. Neurocomputing, 234, pp. 27-37. (SCI; IF=3.241; 27/132 Q1(2017-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
  17. Huang, M.-W., Chen, C.-W.*, Lin, W.-C., Ke, S.-W., and Tsai, C.-F. (2017) SVM and SVM ensembles in Breast Cancer Prediction. PLOS ONE. 12(1), e0161501. (SCI; IF=2.766; 15/64 Q1(2017-JCR) in MULTIDISCIPLINARY SCIENCES)
  18. Tsai, C.-F.*, Lin, W.-C., and Ke, S.-W. (2016) Big Data Mining with Parallel Computing: A Comparison of Distributed and MapReduce Methodologies. Journal of Systems and Software, 122, pp. 83-92. (SCI; IF=2.444; 22/106 Q1(2016-JCR) in COMPUTER SCIENCE, SOFTWARE ENGINEERING)
  19. Huang, M.-W., Lin, W.-C., Chen, C.-W.*, Ke, S.-W., Tsai, C.-F., and Eberle, W. (2016) Data Preprocessing Issues for Incomplete Medical Datasets. Expert Systems, 33(5), pp. 432-438. (SCI; IF=1.180; 59/104 Q3(2016-JCR) in COMPUTER SCIENCE, THEORY & METHODS)
  20. Chen, Z.-Y., Lin, W.-C., Tsai, C.-F.*, and Ke, S.-W. (2016) 3D Model Retrieval by Sample Based Alignment. Journal of Visual Communication and Image Representation, 40, pp. 721-731. (SCI; IF=2.164; 61/146 Q2(2016-JCR) in COMPUTER SCIENCE, SOFTWARE ENGINEERING)
  21. Ke, S.-W., Lin, W.-C., and Tsai, C.-F.* (2016) Research Performance of AACSB Accredited Institutions in Taiwan: Before versus After Accreditation. SpringerPlus, 5(1), pp. 1285-1294. (SCI; IF=1.130; 30/64 Q2(2016-JCR) in MULTIDISCIPLINARY SCIENCES)
  22. Shen, C.-C., Hu, Y.-H., Lin, W.-C., Tsai, C.-F.*, and Ke, S.-W. (2016) Research Impacts of General and Funded Papers: A Citation Analysis of Two ACM International Conference Proceeding Series. Online Information Review, 40(4), pp. 472-480. (SCI/SSCI; 1.534; 31/85 Q2(2016-JCR) in INFORMATION SCIENCE & LIBRARY SCIENCE)
  23. Lin, W.-C., Ke, S.-W., and Tsai, C.-F.* (2016) Robustness and Reliability Evaluations of Image Annotation. Imaging Science Journal, 64(2), pp. 94-99. (SCI; IF=0.451; 25/26 Q4(2015-JCR) in IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY)
  24. Lin, W.-C., Tsai, C.-F.*, Chen, Z.-Y., and Ke, S.-W. (2016) Keypoint Selection for Efficient Bag-of-Words Feature Generation and Effective Image Classification. Information Sciences, 329, pp. 33-51. (SCI; IF=4.832; 7/146 Q1(2016-JCR) in COMPUTER SCIENCE, INFORMATION SYSTEMS)
  25. Lin, W.-C., Ke, S.-W., and Tsai, C.-F.* (2016) SAFQuery: A Simple and Flexible Advanced Web Search Interface. The Electronic Library, 34(1), pp.155-168. (SSCI; IF=0.484; 63/85 Q3(2016-JCR) in INFORMATION SCIENCE & LIBRARY SCIENCE)
  26. Lin, W.-C., Tsai, C.-F.*, Ke, S.-W., and You, M.-L. (2015) On Learning Dual Classifiers for Better Data Classification. Applied Soft Computing, Special Issue on Soft Computing for Big Data, 37, pp. 296-302. (SCI; IF=2.857; 21/130 Q1(2015-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
  27. Chen, Z.-Y., Lin, W.-C., Ke, S.-W., and Tsai, C.-F.* (2015) Evolutionary Feature and Instance Selection for Traffic Sign Recognition. Computers in Industry, Special Issue on Synergy of Computers, Cognition, Communication and Control with Industrial Applications, 74, pp. 201-211.  (SCI; IF=1.685; 44/104 Q2(2015-JCR) in COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS)
  28. Lin, W.-C., Chen, Z.-Y., Ke, S.-W., Tsai, C.-F.*, and Lin, W.-Y. (2015) The Effect of Low-Level Image Features on Pseudo Relevance Feedback. Neurocomputing, 166, pp. 26-37. (SCI; IF=2.392; 31/130 Q1(2015-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
  29. Chen, C.-W., Lin, W.-C., Ke, S.-W., Tsai, C.-F.*, and Hu, Y.-H. (2015) On Mining Incomplete Medical Datasets: Ordering Imputation and Classification. Technology and Health Care, 23(5), pp. 619-625. (SCI; IF=0.678; 68/76 Q4(2015-JCR) in ENGINEERING, BIOMEDICAL)
  30. Lin, W.-C., Tsai, C.-F.*, Ke, S.-W., Hung, C.-W., and Eberle, W. (2015) Learning to Detect Representative Data for Large Scale Instance Selection. Journal of Systems and Software, 106, pp. 1-8. (SCI; IF=1.424; 24/106 Q1(2015-JCR) in COMPUTER SCIENCE, SOFTWARE ENGINEERING)
  31. Lin, W.-C., Tsai, C.-F.*, and Ke, S.-W. (2015) Correlation Analysis for Comparison of the Citation Impact of Journals, Magazines, and Conferences in Computer Science. Online Information Review, 39(3), pp. 310-325. (SCI/SSCI; IF=1.152; 71/143 Q2(2015-JCR) in COMPUTER SCIENCE, INFORMATION SYSTEMS)
  32. Chen, Z.-Y., Tsai, C.-F.*, Eberle, W., Lin, W.-C., and Ke, S.-W. (2015) Instance Selection by Genetic-Based Biological Algorithm. Soft Computing, 19(5), pp. 1269-1282. (SCI; IF=1.630; 56/130 Q2(2015-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
  33. Lin, W.-C., Ke, S.-W., and Tsai, C.-F.* (2015) CANN: An Intrusion Detection System Based on Combining Cluster Centers and Nearest Neighbors. Knowledge-Based Systems, 78, pp. 13-21. (SCI; IF=3.325; 17/130 Q1(2015-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
  34. Hu, Y.-H., Lin, W.-C., Tsai, C.-F.*, Ke, S.-W., and Chen, C.-W. (2015) An Efficient Data Preprocessing Approach for Large Scale Medical Data Mining. Technology and Health Care, 23(2), pp. 153-160. (SCI; IF=0.678; 68/76 Q4(2015-JCR) in ENGINEERING, BIOMEDICAL)
  35. Ke, S.-W., Lin, W.-C., Tsai, C.-F.*, and Hu, Y.-H. (2014) Citation Impact Analysis of Research Papers that Appear in Oral and Poster Sessions: A Case Study of Three Computer Science Conferences. Online Information Review, 38(6), pp. 738-745. (SCI/SSCI; IF=0.918; 34/85 Q2(2014-JCR) in INFORMATION SCIENCE & LIBRARY SCIENCE)
  36. Lin, W.-C., Tsai, C.-F.*, and Ke, S.-W. (2014) Dimensionality and data reduction in telecom churn prediction. Kybernetes, 43(5), pp. 737-749. (SCI; IF=0.429; 24/24 Q4(2014-JCR) in COMPUTER SCIENCE, CYBERNETICS)
  37. Tsai, C.-F.*, and Lin, W.-C. (2012) Scenery Image Retrieval by Meta-Feature Representation. Online Information Review, 36(4), pp. 517-533. (SCI/SSCI; IF=0.939; 37/85 Q2(2012-JCR) in INFORMATION SCIENCE & LIBRARY SCIENCE)
  38. Tsai, C.-F.*, Lin, W.-C., and Hung, C. (2011) Quality Analysis of Object Categorization Benchmarks: Corel, Caltech, and IAPR Datasets. Recent Patents on Computer Science, 4(2), pp. 108-113. (EI)
  39. Lin, W.-C.*, Oakes, M., and Tait, J. (2010) Improving Image Annotation via Representative Feature Vector Selection. Neurocomputing, 73(10-12), pp. 1774-1782. (SCI; IF=1.442; 50/108 Q2(2010-JCR) in COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
  40. Lin, W.-C.*, Oakes, M., Tait, J., and Tsai, C.-F. (2009) Improving image annotation via useful representative feature selection. Cognitive Processing, 10(3), pp. 233-242. (SSCI; IF=1.030; 66/81 Q4(2010-JCR) in PSYCHOLOGY, EXPERIMENTAL)
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