Dr. Jerry Chun-Wei Lin

Assistant Professor
Harbin Institute of Technology, China

Highest Degree
Ph.D. in Computer Science and Information Engineering from National Cheng Kung University, Tainan, Taiwan

My URL
https://livedna.org/886.9738

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Biography

Dr. Jerry Chun-Wei Lin is currently an Assistant Professor at Innovative Information Industry Research Center (IIIRC) at School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, China. He was Graduated and earned his Ph.D. degree with major in Computer Science and Information Engineering from National Cheng Kung University, Tainan, Taiwan in 2010. His research interests include Data Mining, Machine Learning, Artificial Intelligence, and Social Computing, Multimedia and Image Processing and Privacy-Preserving and Security Technologies. He is also serving as reviewer for number of journals. He has published 2 books, 57 research articles in journals as well as 70 conference papers contributed as author/co-author.

Area of Interest:

Computer Sciences
Data Mining
Machine Learning
Artificial Intelligence
Image Processing

Selected Publications

  1. Lin, J.C.W., W. Gan, T.P. Hong and J. Zhang, 2015. Updating the built prelarge fast updated sequential pattern trees with sequence modification. Int. J. Data Warehouse. Min., 11: 1-22.
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  2. Lin, J.C.W., W. Gan, T.P. Hong and B. Zhang, 2015. An incremental high-utility mining algorithm with transaction insertion. Sci. World J., 10.1155/2015/161564.
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  3. Lin, J.C.W., T.P. Hong and T.C. Lin, 2015. A CMFFP-tree algorithm to mine complete multiple fuzzy frequent itemsets. Applied Soft Comput., 28: 431-439.
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  4. Lin, J.C.W., T.P. Hong and G.C. Lan, 2015. Updating the Sequential Patterns in Dynamic Databases for Customer Sequences Deletion. J. Internet Technol., 16: 370-379.
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  5. Lin, J.C.W., G.C. Lan, T.P. Hong and Y.Y. Wang, 2015. A fast updated high utility pattern trees for transaction deletion. J. Internet Technol., 16: 131-138.
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  6. Lin, C.W., T.P. Hong, K.T. Yang and S.L. Wang, 2015. The ga-based algorithms for optimizing hiding sensitive itemsets through transaction deletion. Appl. Intell., 42: 210-230.
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  7. Lin, C.W., Lan, G.C and T.P. Hong, 2015. Mining high utility itemsets for transaction deletion in a dynamic database. Intell. Data Anal., 19: 43-55.
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  8. Lan, G.C., T.P. Hong, H.Y. Lee and C.W. Lin, 2015. Tightening upper bounds for mining weighted frequent itemsets. Intell. Data Anal., 19: 413-419.
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  9. Zhang, B., C.W. Lin, W. Gan and T.P. Hong, 2014. Maintaining the discovered sequential patterns for sequence insertion in dynamic databases. Eng. Appl. Artif. Intell., 35: 131-142.
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  10. Xu, L., C.W. Lin, G.C. Lan and T.P. Hong, 2014. Evaluating the Side-Effects of Privacy Preserving Sequential Pattern Mining for Sequence Deletion. ICIC Express Lett., 8: 535-540.

  11. Lin, J.C.W., W. Gan and T.P. Hong, 2014. Efficiently maintaining the fast updated sequential pattern trees with sequence deletion. IEEE Access, 2: 1374-1383.
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  12. Lin, C.W., W. Gan, T.P. Hong, S.O. Park and B.W. Chen, 2014. Peer-to-peer usage analysis in dynamic databases. Peer-Peer Networking Appl., 10.1007/s12083-014-0290-2.
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  13. Lin, C.W., T.P. Hong, W.Y. Lin and G.C. Lan, 2014. Efficient updating of sequential patterns with transaction insertion. Intell. Data Anal., 18: 1013-1026.
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  14. Lin, C.W., T.P. Hong, J.W. Wong, G.C. Lan and W.Y. Lin, 2014. A ga-based approach to hide sensitive high utility itemsets. Sci. World J., 10.1155/2014/804629.
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  15. Lin, C.W., T.P. Hong, G.C. Lan, J.W. Wong and W.Y. Lin, 2014. Incrementally mining high utility patterns based on pre-large concept. Appl. Intell., 40: 343-357.
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  16. Lin, C.W., T.P. Hong and H.C. Hsu, 2014. Reducing side effects of hiding sensitive itemsets in privacy preserving data mining. Sci. World J., 10.1155/2014/235837.
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  17. Lin, C.W., B. Zhang, K.T. Yang and T.P. Hong, 2014. Efficiently hiding sensitive itemsets with transaction deletion based on genetic algorithms. Sci. World J., 10.1155/2014/398269.
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  18. Lin, C.W and T.P. Hong, 2014. Mining fuzzy frequent itemsets based on UBFFP trees. J. Intell. Fuzzy Syst., 27: 535-548.
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  19. Lin, C.W and T.P. Hong, 2014. Maintenance of prelarge trees for data mining with modified records. Inf. Sci., 278: 88-103.
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  20. Li, C. R., C.W. Lin, W. Gan and T.P. Hong, 2014. A Modified Maintenance Algorithm for Updating FUSP Tree in Dynamic Database. In: Modern Advances in Applied Intelligence. Ali, M., P. Jeng-Shyang, C. Shyi-Ming and H. Mong-Fong.(Ed.). Springer International Publishing, Switzerland, pp: 301-310.
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  21. Kong, L., C.M. Chen, H.C. Shih, C.W. Lin, B.Z. He and J.S. Pan, 2014. An energy-aware routing protocol using cat swarm optimization for wireless sensor networks. In: Advanced Technologies, Embedded and Multimedia for Human-Centric Computing. Huang, Yueh-Min., C. Han-Chieh , D. Der-Jiunn, J.J.H.P. James.(Ed.). Springer, Netherlands, pp: 311-318.
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  22. Kan, W., T.Y. Wu, T. Han, C.W. Lin, C.M. Chen and J.S. Pan, 2014. An Efficient Detecting Mechanism for Cross-Site Script Attacks in the Cloud. In: Advanced Technologies, Embedded and Multimedia for Human-centric Computing. Huang, Yueh-Min., C. Han-Chieh , D. Der-Jiunn, J.J.H.P. James.(Ed.). Springer, Netherlands, pp: 663-672.
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  23. Hong, T.P., C.W. Lin and T.C. Lin, 2014. The mffp-tree fuzzy mining algorithm to discover complete linguistic frequent itemsets. Comput. Intell., 30: 145-166.
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  24. Chen, Y.Y., Y.Y. Wang and C.W. Lin, 2014. MABLIPS: Development of Agent-Based Vehicle Location Tracking System. In: Advanced Technologies, Embedded and Multimedia for Human-centric Computing. Huang, Yueh-Min., C. Han-Chieh , D. Der-Jiunn, J.J.H.P. James.(Ed.). Springer, Netherlands, pp: 1159-1166.
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  25. Vo, B., C.W. Lin, T.P. Hong, V.V. Vu, M. Nguyen and B. Le, 2013. An Efficient Method for Hiding High Utility Itemsets. Front. Artif. Intell. Appl., 252: 356-363.
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  26. Lin, C.W., T.P. Hong, Y.F. Chen, C.W. Lin and S.T. Pan, 2013. An integrated mffp-tree algorithm for mining global fuzzy rules from distributed databases. J. Universal Comput. Sci., 19: 521-538.
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  27. Lin, C.W., T.P. Hong, C.C. Chang and S.L. Wang, 2013. A greedy-based approach for hiding sensitive itemsets by transaction insertion. J. Inf. Hiding Multimedia Signal Process., 4: 201-227.
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  28. Lin, C.W. and T.P. Hong, 2013. A Survey of Fuzzy Web Mining. Wiley Interdiscip. Rev. Data Min. Knowl. Discovery 3: 190-199.
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  29. Hong, T.P., S.D. Li, Y.C. Lee and C.W. Lin, 2013. Dynamic Scheduling with Mold Constraints. ICIC Express Lett., 7: 1233-1238.

  30. Hong, T.P., C.W. Lin, K.T. Yang and S.L. Wang, 2013. Using TF-IDF to hide sensitive itemsets. Appl. Intell., 38: 502-510.
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  31. Lin, C.W., G.C. Lan and T.P. Hong, 2012. An incremental mining algorithm for high utility itemsets. Expert Syst. Appl., 39: 7173-7180.
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  32. Lin, C.W and T.P. Hong, 2012. A new mining approach for uncertain databases using CUFP trees. Expert Syst. Appl., 39: 4084-4093.
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  33. Hong, T.P., C.W. Lin, T.C. Lin, Y.F. Chen and S.T. Pan, 2012. Integration of multiple fuzzy FP-trees. In: Intelligent Information and Database Systems. P. Jeng-Shyang, C. Shyi-Ming, T.N. Ngoc.(Ed.). Springer, Berlin Heidelberg, pp: 330-337.
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  34. Lin, C.W., T.P. Hong and W.H. Lu, 2011. An effective tree structure for mining high utility itemsets. Expert Syst. Appl., 38: 7419-7424.
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  35. Lin, C.W and T.P. Hong, 2011. Temporal data mining with up-to-date pattern trees. Expert Syst. Appl., 38: 15143-15150.
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  36. Hong, T.P., T.I. Chien, Y.L. Wu and C.W. Lin, 2011. Evolutionary Computation for Good Makespans of Scheduling Problems with Mold Constraints. ICIC Express Lett., 5: 1893-1898.

  37. Hong, T.P., C.W. Lin, K.T. Yang and S.L. Wang, 2011. A heuristic data-sanitization approach based on TF-IDF. In: Modern Approaches in Applied Intelligence. Mehrotra, K.G., K.M. Chilukuri, C.O. Jae, K.V. Pramod, A. Moonis.(Ed.). Springer, Berlin Heidelberg, pp: 156-164.
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  38. Lin, C.W., T.P. Hong and W.H. Lu, 2010. Using the structure of prelarge trees to incrementally mine frequent itemsets. New Gener. Comput., 28: 5-20.
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  39. Lin, C.W., T.P. Hong and W.H. Lu, 2010. Linguistic data mining with fuzzy FP-trees. Expert Syst. Appl., 37: 4560-4567.
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  40. Lin, C.W., T.P. Hong and W.H. Lu, 2010. Efficiently mining high average utility itemsets with a tree structure. In: Intelligent Information and Database Systems. Nguyen, N.T., T.L. Manh, S. Jerzy. (Ed.). Springer, Berlin Heidelberg, pp: 131-139.
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  41. Lin, C.W., T.P. Hong and W.H. Lu, 2010. Efficient Modification of Fast Updated FP-trees Based on Pre-large Concepts. Int. J. Innovative Comput. Inf. Control, 6: 5163-5177.

  42. Lin, C.W., T.P. Hong and W.H. Lu, 2010. An efficient tree-based fuzzy data mining approach. Int. J. Fuzzy Sys., 12: 150-157.
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  43. Hong, T.P., C.Y. Wang and C.W. Lin, 2010. Providing timely updated sequential patterns in decision making. Int. J. Inf. Technol. Decis. Making, 9: 873-888.
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  44. Chen, Y.Y., Y.Y. Wang, W.L. Wang and C.W. Lin, 2010. An Introduction of a Push System for Bicycle Position. J. Far East Univ., 27: 305-314.

  45. Lin, C.W., T.P. Hong and W.Hsiang, 2009. Maintenance of the Pre- large Trees for Record Deletion Lect. Notes Electr. Eng., 11: 137-148.
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  46. Lin, C.W., T.P. Hong and W.H. Lu, 2009. The Pre-FUFP algorithm for incremental mining. Expert Syst. Appl., 36: 9498-9505.
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  47. Hong, T.P., C.W. Lin and Y.L. Wu, 2009. Maintenance of fast updated frequent pattern trees for record deletion. Comput. Stat. Data, 53: 2485-2499.
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  48. Lin, C.W., T.P. Hong and W.Hsiang, 2008. Incremental Mining with Prelarge Trees Lect. Notes Comput. Sci., 5027: 169-178.
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  49. Hong, T.P., C.W. Lin and Y.L. Wu, 2008. Incrementally fast updated frequent pattern trees. Expert Syst. Appl., 34: 2424-2424.
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  50. Hong, T.P., C.W. Lin and Y.L. Wu, 2008. An Efficient FUFP-tree Maintenance Algorithm for Record Modification. Int. J. Innovative Comput. Inf. Control, 4: 2875-2887.

  51. Lin, C.W., T.P. Hong, W.H. Lu and C.H. Wu, 2007. Maintenance of fast updated frequent trees for record deletion based on prelarge concepts. Trends Appl. Artif. Intell., 4570: 675-684.
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