林浚玮
通讯地址
深圳市西丽大学城哈工大校区D栋424 (518055)

电子邮件
jerrylin@ieee.org
联系电话
075526033148
个人简介      
林浚玮博士,哈尔滨工业大学(深圳)副教授,深圳市海外高层次B类人才(孔雀计划),国立成功大学资讯工程系工学博士。其研究经历与特色兼具学术界经验(高校助理教授、副教授),工业界经验(富士康集团资深工程师)和国际经验(澳大利亚,中国台湾,中国大陆)。林博士课题组的主要研究方向为: 数据挖掘、人工智能、机器学习与隐私安全等,至今已接收并发表200余篇高水平论文(74篇SCI期刊论文与110余篇EI会议论文),其中JCR一区期刊30篇,JCR二区以上期刊45篇。根据Google Scholar统计,目前论文总引用1200余次,H-index为16。近五年来,先后主持了国家自然科学青年基金、CCF-腾讯犀牛鸟青年基金、CCF-腾讯犀牛鸟创意基金、哈工大-腾讯联合基金、哈工大重点创新项目培育计划等科研项目。其学术任职包括: 从2016年起担任数据挖掘领域的知名SCI期刊Intelligent Data Analysis的编委Editorial Board Member,和国际期刊Data Science and Pattern Recognition的主编。他是数十个国际知名学术期刊的审稿人,同时担任数十个国际会议的程序委员会委员和审稿人。详细信息请访问智能型知识工程实验室网站: http://ikelab.net
研究方向      
数据挖掘、大数据技术、人工智能、机器学习、云计算、 物联网等。
林博士课题组每年招收硕士生4名左右,欢迎有志于以上研究领域的优秀学生加入,有志于学术科研或工程应用均可以,感兴趣请联系 jerrylin@ieee.org。

详细信息请访问智能型知识工程实验室网站: http://ikelab.net
教育经历      
2006 - 2010
获工学博士学位 (资讯工程系),国立成功大学
2004 - 2006
获管理学硕士学位 (资讯管理),台湾义守大学
2003 - 2004
硕士 (肆业),澳大利亚新南威尔士大学
1998 - 2002
获管理学学士学位 (资讯管理),台湾义守大学
研究与工作经历    
2017/01 -
副教授、硕士生导师,哈工大(深圳) 计算机科学与技术学院
2012/10 -2016/12
助理教授、硕士生导师,哈工大(深圳) 计算机科学与技术学院
2012/3-2012/10
资深工程师,鸿海(富士康)科技股份有限公司
2011 - 2012
博士后研究员,台湾高雄大学资讯工程系
2011 - 2012
兼任助理教授,台湾屏东科技大学资讯管理系
2010 - 2011
专案助理研究员,台湾高雄大学通识教育中心
2010 - 2012
兼任助理教授,台湾高雄大学资讯工程系
2009 - 2010
兼任讲师,台湾正修科技大学资讯管理系
专业资质与学术兼职    
2010-
IEEE 会员,ACM会员,CCF会员
2013-
深圳市海外高层次B类人才(孔雀计划)
2016-
国际期刊Data Science and Pattern Recognition,主编Editor-in-chief
2016-
SCI期刊Intelligent Data Analysis,编委Editorial Board Member
2010-
国际期刊审稿人 (SCI). IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), International Journal of Software Engineering and Knowledge Engineering, WIREs Data Mining and Knowledge Discovery, IEEE System Journal, The Scientific World Journal, Expert Systems with Applications, Information Sciences, Soft Computing, Scientific Research and Essays, Knowledge-Based Systems, Knowledge and Information Systems, Journal of Information Science and Engineering, Neurocomputing
2010-
国际会议分会主席 (Session Chair). ICICIC 2010, NCWIA 2011, IEEE GrC 2011, IBICA 2011, ISKE 2013, ECC 2014, ITAOI 2015, MISNC 2016, MISNC 2017
2009-
国际会议程序委员与审稿人. IEEE GrC 2009, NDT 2009, IEEE GrC2010, NDT 2010, WMSCI 2010, SMC 2010, ICARCV 2010, SICT 2010, NCM 2010, CICN2010, TAAI 2010, ICIMA 2010, ICS 2010, ICCIT 2010, ISDA 2010, NDT 2011, GrC 2011, CSNT 2011, WICT 2011, SMC 2011, IDCTA 2011, ICADIWT 2011, CCS 2011, ICDIM 2011, TAAI 2011, SocProS 2011, ICIPM 2011, WICT 2013, KSE 2013, KMO 2013, CYBCON 2013, IEEE GrC 2013, TAAI 2013, ICSEC 2013, HAIS 2013, INTELLI 2013, WICT 2014, SocPar 2014, ISDA 2014, cascon 2014, BICTA 2014, IEEE SMC 2014, ICSEC 2014, KiSE 2014, IEEE GrC 2014, NaBIC 2014, CASoN 2014, BICTA 2014, MISNC 2014, ICGEC 2014, TAAI 2014, PRICAI 2014, ICETI 2014, TAAI 2014, ECC 2014, ICEASA 2014, ACIIDS 2015, PAKDD 2015, PlatCon 2015, IMETI 2015
科研项目    
2016.01-2018.12
国家自然科学青年基金 (主持)
2016.10-2018.10
广东省清远市项目 (核心参与)
2016.01-2017.12
CCF-腾讯犀牛鸟创意基金 (主持)
2015.12-2016.11
哈工大-腾讯合作项目 (主持)
2014.10-2015.10
CCF-腾讯犀牛鸟科研基金 (主持)
2014.01-2015.12
哈工大重点创新项目培育计划 (主持)
2014.01-2015.12
哈工大科研创新研究基金 (主持)
2012.01-2015.12
深圳市海外高层次人才创新创业专项基金项目:深圳市孔雀计划 (核心参与)
科研成果及奖励    
2016
国际会议Industrial ICDM最佳海报提名奖
2016
国际会议ACM SIGAPP SAC最佳海报提名奖
2015
国际会议ICGEC最佳论文奖
2015
国际会议MLDM最佳论文提名奖
2014
CCF-腾讯犀牛鸟青年基金-优秀奖
2014
国际会议IEA/AIE最佳论文奖
2013
台湾网路智能学会的最佳硕士论文指导教授奖
2013
深圳市海外高层次B类人才(孔雀计划)
2011
台湾网路智能学会的最佳硕士论文指导教授奖
2011
台湾网路智能学会的最佳博士论文奖
2011
台湾人工智慧学会的博士论文奖佳作
2007
国际会议ICICIC最佳论文奖
发明专利    
[1]. M447011, 王月云, 林浚玮, 计程车之安全通报系统, 2014.4.21-2023.12.30 (台湾发明专利)

[2]. 吴祖扬, 陈建铭, 林浚玮等. 云环境下的数据分层访问方法及系统, 授权号CN104320426, 2015. (国家发明专利)

[3]. 林浚玮, 潘正祥, 吴祖扬, 陈建铭, 罗牧之. 具有改善视线功能的车用装置, 授权号CN104354571A, 2015. (国家发明专利)

[4]. 林浚玮, 甘文生等. 项集挖掘方法及装置, 申请号201510115234.5, 2015. (国家发明专利)

[5]. 林浚玮, 甘文生等. 数据挖掘方法和装置, 申请号201510115234.5, 2015. (国家发明专利)

[6]. 林浚玮, 甘文生等. 项集挖掘方法及装置, 申请号201510106336.0, 2015. (国家发明专利)

[7]. 林浚玮, 甘文生等. 一种对象信息的展示方法和装置, 申请号201510106783.6, 2015. (国家发明专利)

[8]. 林浚玮, 甘文生等. 一种模式挖掘方法及装置, 申请号201610856770.5, 2016. (国家发明专利)
论文及著作    
林教授至今已发表200余篇高水平学术论文 (74篇SCI期刊论文与110多篇国际会议论文),其中JCR一区期刊30篇,JCR二区以上期刊45篇。根据Google Scholar统计,目前论文总引用1200余次,H-index为16。详细信息请访问智能型知识工程实验室网站: http://ikelab.net

出版著作情况:

[1]. "Tree-based Algorithms for Incremental, Utility, and Fuzzy Data Mining", Lambert Academic Publisher, 2015. (主编/排名第1)

[2]. "TGenetic and Evolutionary Computing - Volume I", Proceeding of the Eighth International Conference on Genetic and Evolutionary Computing, ICGEC 2014, Springer, 2014. (主编/排名第3)

[3]. "Genetic and Evolutionary Computing - Volume I", Proceeding of the Ninth International Conference on Genetic and Evolutionary Computing, ICGEC 2015, Springer, 2014. (主编/排名第2)

[4]. "Genetic and Evolutionary Computing - Volume II", Proceeding of the Ninth International Conference on Genetic and Evolutionary Computing, ICGEC 2015, Springer, 2014. (主编/排名第2)

[5]. "A Survey of Fuzzy Data Mining Techniques", Springer, 2016. (参编/排名第3)

[6]. "Genetic and Evolutionary Computing - Volume II", Proceeding of the Tenth International Conference on Genetic and Evolutionary Computing, ICGEC 2016, Springer, 2016. (主编/排名第2)



下面仅列出近两年2015/01 - 2017/02的主要期刊论文。

1. Wensheng Gan, Jerry Chun-Wei Lin*, Philippe Fournier-Viger, and Han-Chieh Chao, “Extracting Recent Weighted-based Patterns from Uncertain Temporal Databases,” Engineering Applications of Artificial Intelligence, 2017. (SCI/EI, IF:2.368, JCR Q1)
2. Wensheng Gan, Jerry Chun-Wei Lin*, Philippe Fournier-Viger, Han-Chieh Chao, and Justin Zhan “Mining of Frequent Patterns with Multiple Minimum Supports,” Engineering Applications of Artificial Intelligence, 2017 (SCI/EI, IF:2.368, JCR Q1)
3.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Han-Chieh Chao, and Tzung-Pei Hong, “Efficiently Mining Frequent Itemsets with Weight and Recency Constraints,” Applied Intelligence, 2017. (SCI/EI, IF:1.215, JCR Q3)
4. Jeng-Shyang Pan, Jerry Chun-Wei Lin*, Lu Yang, Philippe Fournier-Viger, and Tzung-Pei Hong, “Efficiently Mining of Skyline Frequent-Utility Patterns,” Intelligent Data Analysis, 2017. (SCI/EI, IF: 0.631, JCR Q4)
5.Jerry Chun-Wei Lin, Shifeng Ren, Philippe Fournier-Viger, Tzung-Pei Hong, Ja-Hwung Su, and Bay Vo, “A Fast Algorithm for Mining High Average-Utility Itemsets,” Applied Intelligence, 2017. (SCI/EI, IF:1.215, JCR Q3)
6.Jimmy Ming-Thai Wu, Justin Zhan, and Jerry Chun-Wei Lin*, “An ACO-based Approach to Mine High-Utility Itemsets,” Knowledge-Based Systems, Vol. 116, pp. 102-113, 2017. (SCI/EI, IF:3.325, JCR Q1)
7.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong, and Justin Zhan, "Efficient Mining of High-Utility Itemsets Using Multiple Minimum Utility Thresholds," Knowledge-Based Systems, Vol. 113, pp. 100-115, 2016. (SCI/EI, IF:3.325, JCR Q1)
8.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, and Tzung-Pei Hong, “FDHUP: Fast Algorithm for Mining Discriminative High Utility Patterns,” Knowledge and Information Systems, pp. 1-37, 2016. (SCI/E, IF: 1.702, JCR Q2)
9.Jerry Chun-Wei Lin, Philippe Fournier-Viger, and Wensheng Gan, “FHN: An Efficient Algorithm for Mining High-Utility Itemsets with Negative Unit Profits,” Knowledge-Based Systems, Vol. 111, pp. 283-298, 2016. (SCI/EI IF:3.325, JCR Q1)
10.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger and Tzung-Pei Hong, “Efficiently Updating the Discovered Sequential Patterns for Sequence Modification,” International Journal of Software Engineering and Knowledge Engineering, Vol. 26 (8), pp. 1285-1313, 2016. (SCI/EI, IF:0.240, JCR Q4)
11. Souleymane Zida, Philippe Fournier-Viger, Jerry Chun-Wei Lin, Cheng-Wei Wu, Vincent S. Tseng, “EFIM: A Fast and Memory Efficient Algorithm for High-Utility Itemset Mining,” Knowledge and Information Systems, pp. 1-31, 2016. (SCI/EI, IF: 1.702, JCR Q2)
12.Jerry Chun-Wei Lin, Qiankun Liu, Philippe Fournier-Viger, and Tzung-Pei Hong, “PTA: An Efficient System for Anonymizing Transaction Databases”, IEEE Access, Vol. 4, pp. 6467-6479, 2016. (SCI/EI, IF:1.248, JCR Q2)
13.Jerry Chun-Wei Lin, Ting Li, Philippe Fournier-Viger, Tzung-Pei Hong, Jimmy Ming-Thai Wu, and Justin Zhan “Efficient Mining of Multiple Fuzzy Frequent Itemsets,” International Journal of Fuzzy Systems, pp. 1-9, 2016. (SCI/EI, IF: 0.941, JCR Q3)
14.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong, and Vincent S. Tseng, "Efficiently Mining Uncertain High-Utility Itemsets," Soft Computing, pp. 1-20, 2016. (SCI/EI, IF:1.630, JCR Q2)
15.Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Tzung-Pei Hong, and Miroslav Voznak “A Binary PSO Approach to Mine High-Utility Itemsets” Soft Computing, pp. 1-19, 2016. (SCI/EI, IF:1.630, JCR Q2)
16.Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Ming-Thai Wu, Tzung-Pei Hong, Leon Shyue-Liang Wang, and Justin Zhan, "Mining High-Utility Itemsets based on Particle Swarm Optimization," Engineering Applications of Artificial Intelligence, Vol. 55, pp. 320-330, 2016. (SCI/EI, IF:2.368, JCR Q1)
17.Jerry Chun-Wei Lin, Tsu-Yang Wu, Philippe Fournier-Viger, Guo Lin, Justin Zhan and Miroslav Voznak, “Fast Algorithms for Hiding Sensitive High-Utility Itemsets in Privacy-Preserving Utility Mining,” Engineering Applications of Artificial Intelligence, Vol. 55, pp. 269-284, 2016. (SCI/EI, IF:2.368, JCR Q1)
18.Chun-Wei Lin, Binbin Zhang, Wensheng Gan, Bo-Wei Chen, Seungmin Rho, Tzung-Pei Hong, “Updating High-Utility Pattern Trees with Transaction Modification,” Multimedia Tools and Applications, Vol. 75(9), pp. 4887-4912, 2016. (SCI/EI, IF:1.313, JCR Q2)
19.Peng Cheng, Ivan Lee, Chun-Wei Lin, and Jeng-Shyang Pan, “Association Rule Hiding Based on Evolutionary Multi-objective Optimization,” Intelligent Data Analysis, Vol. 20(3), pp. 495-514, 2016. (SCI/EI, IF: 0.631, JCR Q4)
20.Jerry Chun-Wei Lin, Ting Li, Philippe Fournier-Viger, Tzung-Pei Hong, Justin Zhan, and Miroslav Voznak “An Efficient Algorithm to Mine High Average-Utility Itemsets,” Advanced Engineering Informatics, Vol. 30(2), pp. 233-243, 2016. (SCI/EI, IF:2.00, JCR Q1)
21.Jerry Chun-Wei Lin, Qiankun Liu, Philippe Fournier-Viger, Tzung-Pei Hong, Miroslav Voznak, and Justin Zhan “A Sanitization Approach for Hiding Sensitive Itemsets based on Particle Swarm Optimization,” Engineering Applications of Artificial Intelligence, Vol. 53, pp. 1-18, 2016. (SCI/EI, IF:2.368, JCR Q1)
22.Ra¨ıssa Yapan Dougnon, Philippe Fournier-Viger, Lin, Jerry Chun-Wei Lin, and Roger Nkambou, “Inferring Social Network User Profiles using a Partial Social Graph,” Journal of Intelligent Information Systems, Vol. 47 (2), pp. 313-244, 2016. (SCI/EI, IF: 1.00, JCR Q3)
23.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong, and Vincent S. Tseng, “Fast Algorithms for Mining High-Utility Itemsets with Various Discount Strategies,” Advanced Engineering informatics, Vol. 30(2), pp. 109-126, 2016. (SCI/EI, IF:2.00, JCR Q1)
24.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong, and Vincent S. Tseng, “Efficient Algorithms for Mining High-Utility Itemsets in Uncertain Databases,” Knowledge-Based Systems, Vol. 96, pp. 171-187, 2016. (SCI/EI, IF:3.325, JCR Q1)
25.Jerry Chun-Wei Lin, Wensheng Gan, and Tzung-Pei Hong, “A Fast Maintenance Algorithm of the Discovered High-Utility Itemsets with Transaction Deletion,” Intelligent Data Analysis, Vol. 20(4), 891-913, 2016. (SCI, IF: 0.631, JCR Q4)
26.Jerry Chun-Wei Lin, Wensheng Gan, Tzung-Pei Hong, Hsin-Yi Chen and Sheng-Tun Li, “An Efficient Algorithm to Maintain the Discovered Frequent Sequences with Record Deletion,” Intelligent Data Analysis, Vol. 20(3), pp. 655-677, 2016. (SCI, IF: 0.631, JCR Q4)
27.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong, and Vincent S. Tseng, “Weighted Frequent Itemset Mining over Uncertain Databases,” Applied Intelligence, Vol. 44(1), pp. 232-250, 2016. (SCI/EI, IF:1.215, JCR Q3)
28. Chun-Wei Lin, Wensheng Gan, and Tzung-Pei Hong, “Maintaining the Discovered High-Utility Itemsets with Transaction Modification,” Applied Intelligence, Vol. 44(1), pp. 166-178, 2016. (SCI/EI, IF:1.215, JCR Q3)
29. Peng Cheng, John F. Roddick, Shu-Chuan Chu, and Chun-Wei Lin, “Privacy Preservation through a Greedy, Distortion-based Rule-Hiding Method,” Applied Intelligence, Vol. 44(2), pp. 295-306, 2016. (SCI/EI, IF:1.215, JCR Q3)
30.Jerry Chun-Wei Lin, Tzung-Pei Hong, Tsung-Ching Lin and Shing-Tai Pan, “An UBMFFP Tree for Mining Multiple Fuzzy Frequent Itemsets,” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 23(6), pp. 861-879, 2015. (SCI/EI, IF:1.00, JCR Q3)
31.Peng Cheng, Chun-Wei Lin, Jeng-Shyang Pan, and Ivan Lee, “Manage the Tradeoff in Data Sanitization,” IEICE Transactions on Information and Systems, Vol.E98-D (10), pp.1856-1860, 2015. (SCI/EI, IF:0.226, JCR Q4)
32.Jerry Chun-Wei Lin, Ting Li, Philippe Fournier-Viger, and Tzung-Pei Hong, “A Fast Algorithm for Mining Fuzzy Frequent Itemsets,” Journal of Intelligent & Fuzzy Systems, Vol. 29(6), pp. 2373-2379, 2015. (SCI/EI, IF:1.004, JCR Q3)
33.Jerry Chun-Wei Lin, Wensheng Gan, Tzung-Pei Hong, and Vincent S. Tseng, “Efficient Algorithms for Mining Up-to-Date High-Utility Patterns,” Advanced Engineering Informatics, Vol. 29(3), pp. 648-661, 2015. (SCI/EI, IF:2.00, JCR Q1)
34.Jerry Chun-Wei Lin, Wensheng Gan, and Tzung-Pei Hong, “A Fast Updated Algorithm to Maintain the Discovered High-Utility Itemsets for Transaction Modification,” Advanced Engineering Informatics, Vol. 29(3), pp. 562-574, 2015. (SCI/EI, IF:2.00, JCR Q1)
35.Jerry Chun-Wei Lin, Tzung-Pei Hong, Wensheng Gan, Hsin-Yi Chen, and Sheng-Tun Li, “Incrementally Updating the Discovered Sequential Patterns based on Pre-large Concept,” Intelligent Data Analysis, Vol. 19(5), pp. 1071-1089, 2015. (SCI/EI, IF:0.631, JCR Q4)
36.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, and Tzung-Pei Hong, “RWFIM: Recent Weighted-Frequent Itemsets Mining,” Engineering Applications of Artificial Intelligence, Vol. 45, pp. 18-32, 2015. (SCI/EI, IF:2.368, JCR Q1)
37. Peng Cheng, Chun-Wei Lin, and Jeng-Shyang Pan, “Use HypE to Hide Association Rules by Adding Items,” PLOS One, Vol. 10(6), pp. 1-19, 2015. (SCI, IF:3.057, JCR Q1)
38. Guo-Cheng Lan, Tzung-Pei Hong, Hong-Yu Lee, and Chun-Wei Lin, “Tightening Upper Bounds for Mining Weighted Frequent Itemsets”, Intelligent Data Analysis, Vol. 19(2), pp. 413-429, 2015. (SCI/EI, IF:0.631, JCR Q4)
39.Jerry Chun-Wei Lin, Tzung-Pei Hong, and Guo-Cheng Lan, “Updating the Sequential Patterns in Dynamic Databases for Customer Sequences Deletion,” Journal of Internet Technology, Vol.16(3), pp.370-379, 2015. (SCI/EI, IF:0.533, JCR Q4)
40. Chun-Wei Lin, Guo-Cheng Lan, and Tzung-Pei Hong, “Mining High Utility Itemsets for Transaction Deletion in a Dynamic Database,” Intelligent Data Analysis, Vol. 19(1), pp. 43-255, 2015. (SCI/EI, IF:0.631, JCR Q4)
41.Jerry Chun-Wei Lin, Tzung-Pei Hong, and Tsung-Ching Li, “A CMFFP-tree Algorithm to Mine Complete Multiple Fuzzy Frequent Itemsets,” Applied Soft Computing, Vol. 28, pp. 431-439, 2015. (SCI/EI, IF:2.857, JCR Q1)
42.Jerry Chun-Wei Lin, Guo-Cheng Lan, Tzung-Pei Hong, and, Yueh-Yun Wang “A Fast Updated High Utility Pattern Trees for Transaction Deletion,” Journal of Internet Technology, Vol.16(1), pp.131-138, 2015. (SCI, IF:0.533, JCR Q4)
43.Jerry Chun-Wei Lin, Wensheng Gan, Tzung-Pei Hong and Binbin Zhang, “An Incremental High-Utility Mining Algorithm with Transaction Insertion,” The Scientific World Journal, Vol. 2015, Article ID 161564, 2015. (SCI, IF:1.219, JCR Q2)
44. Chun-Wei Lin, Tzung-Pei Hong, Kuo-Tung Yang, and Shyue-Liang Wang, “The GA-based Algorithms for Optimizing Hiding Sensitive Itemsets through Transaction Deletion,” Applied Intelligence, Vol. 42(2), pp. 210-230, 2015. (SCI/EI, IF:1.215, JCR Q2)
45. Chun-Wei Lin, Tzung-Pei Hong, Guo-Cheng Lan, Jia-Wei Wong, and Wen-Yang Lin, “Efficient Updating of Discovered High-Utility Itemsets for Transaction Deletion in Dynamic Databases,” Advanced Engineering Informatics, Vol. 29(1), pp. 16-27, 2015. (SCI/EI, IF:2.00, JCR Q1)
46. Chun-Wei Lin, Wensheng Gan, Tzung-Pei Hong, Seungmin Rho, and Bo-Wei Chen “Peer-to-Peer Usage Analysis in Dynamic Databases,” Peer to Peer Networking and Applications, Vol. 8(5), pp. 851-862, 2015. (SCI/EI, IF:1.00, JCR Q3)
47.Jerry Chun-Wei Lin, Wensheng Gan, Tzung-Pei Hong, and Jingliang Zhang “Updating the Built Prelarge Fast Updated Sequential Pattern Trees with Sequence Modification,” International Journal of Data Warehousing and Mining, Vol. 1(1), pp. 1-21, 2015. (SCI/EI, IF:0.625, JCR Q4)
会议论文及发表演说    
下面仅列出近两年2015/01 - 2017/02的会议论文:

1. Wensheng Gan, Jerry Chun-Wei Lin*, and Han-Chieh Chao, “Mining High-Utility Itemsets with both Positive and Negative Unit Profits from Uncertain Databases,” The Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2017 (PAKDD 2017, Springer EI)
2. Nguyen Bui, Van-Nam Huynh, Chun-Wei Lin, and Loan Nguyen, “Mining Closed High-Utility Itemsets from Uncertain Databases,” The International Symposium on Information and Communication Technology , 2016 (SoICT 2016, ACM, EI)
3.Tzung-Pei Hong, Tsung-Ta Shih, Chun-Wei Lin, and Bay Vo, “Integration of Erasable Itemsets,” International Computer Symposium, 2016 (ICS 2016, IEEE, EI)
4.Jerry Chun-Wei Lin, Shifeng Ren, Philippe Fournier-Viger, Ja-Hwung Su, and Bay Vo, “A More Efficient Algorithm to Mine High Average-Utility Itemsets,” The International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2016 (IIHMSP 2016, IEEE, EI)
5. Tzung-Pei Hong, Kun-Yi Lin, Chun-Wei Lin and Bay Vo, “An Incremental Mining Algorithm for Erasable Itemsets,” The 2016 Conference on Technologies and Applications of Artificial Intelligence, 2016 (TAAI 2016)
6.Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Siddharth Dawar, Vikram Goyal, Ashish Sureka, and Bay Vo, “A More Efficient Algorithm to Mine Skyline Frequent-Utility Patterns,” International Conference on Genetic and Evolutionary Computing, pp. 127-135, 2016. (ICGEC 2016, Springer, EI)
7.Jerry Chun-Wei Lin, Jiexiong Zhang, Philippe Fournier-Viger, Tzung-Pei Hong and Chien-Ming Chen, “Efficient Mining of Short Periodic High-Utility Itemsets,” IEEE International Conference on System Man, and Cybernetics, 2016. (IEEE SMC 2016, IEEE, EI)
8.Philippe Fournier-Viger, Jerry Chun-Wei Lin, Quang-Huy Duong, Thu-Lan Dam, Lukas Sevcik, Dominik Uhrin, Miroslav Voznak, “PFPM: Discovering Periodic Frequent Patterns with Novel Periodicity Measures,” Czech-China Conference, 2016. (ECC 2016, Springer, EI)
9.Jerry Chun-Wei Lin, Ting Li, Philippe Fournier-Viger, Tzung-Pei Hong, and Ja-Hwung Su, “Fast Algorithms for Mining Multiple Fuzzy Frequent Itemsets,” IEEE International Conference on Fuzzy Systems, pp. 2113-2119, 2016. (FUZZ-IEEE 2016, IEEE, EI)
10. Philippe Fournier-Viger, Jerry Chun-Wei Lin, Antonio Gomariz, Ted Gueniche, Azadeh Soltani, Zhihong Deng, and Hoang Thanh Lam, “The SPMF Open-Source Data Mining Library Version 2 and beyond,” The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery, 2016. (ECML-PKDD 2016, LNCS, EI)
11. Wensheng Gan, Jerry Chun-Wei Lin*, Philippe Fournier-Viger, and Han-Chieh Chao, “Mining Recent High Expected Weighted Itemset from Uncertain Databases,” The Asia Pacific Web Conference, 2016. (APWeb 2016, LNCS, EI)
12.Jimmy Ming-Tai Wu, Justin Zhan, and Jerry Chun-Wei Lin*, “Mining of High-Utility Itemsets by ACO Algorithm,” The Multidisciplinary International Social Networks Conference, 2016. (MISNC 2016, ACM, EI)
13.Wensheng Gan, Jerry Chun-Wei Lin*, Philippe Fournier-Viger, Han-Chieh Chao, “Mining Recent High-Utility Patterns from Temporal Databases with Time-Sensitive Constraint,” The International Conference on Big Data Analytics and Knowledge Discovery, pp. 3-18, 2016. (DaWaKa 2016, LNCS, EI)
14.Philippe Fournier-Viger, Jerry Chun-Wei Lin, Cheng-Wei Wu, Vincent S. Tseng, and Usef Faghihi, “Mining Minimal High-Utility Itemsets,” The International Conference on Database and Expert Systems Applications, pp. 88-101, 2016. (DEXA 2016, LNCS, EI)
15.Wensheng Gan, Jerry Chun-Wei Lin*, Philippe Fournier-Viger, and Han-Chieh Chao, “More Efficient Algorithms for Mining High-Utility Itemsets with Multiple Minimum Thresholds,” The International Conference on Database and Expert Systems Application, pp. 71-87, 2016. (DEXA 2016, LNCS, EI)
16.Jerry Chun-Wei Lin, Qiankun Liu, Philippe Fournier-Viger, Tzung-Pei Hong, Justin Zhan and Miroslav Voznak, “An Efficient Anonymous System for Transaction Data,” The Multidisciplinary International Social Networks Conference, pp. 1-6, 2016. (MISNC 2016, ACM, EI)
17.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, and Tzung-Pei Hong, “Efficient Mining of Weighted Frequent Itemsets in Uncertain Databases,” International Conference on Machine Learning and Data Mining, pp. 236-250, 2016. (MLDM 2016, LNCS, EI)
18.Philippe Fournier-Viger, Souleymane Zida, Jerry Chun-Wei Lin, Cheng-Wei Wu, and Vincent S. Tseng, “EFIM-Closed: Fast and Memory Efficient Discovery of Closed High-Utility Itemsets,” International Conference on Machine Learning and Data Mining, pp. 199-213, 2016. (MLDM 2016, LNCS, EI)
19.Jerry Chun-Wei Lin, Ting Li, Philippe Fournier-Viger, Tzung-Pei Hong, and Ja-Hwung Su “Efficient Mining of High Average-Utility Itemsets with Multiple Minimum Thresholds,” Industrial Conference on Data Mining, pp. 14-28, 2016. (ICDM 2016, LNCS, EI)
20.Philippe Fournier-Viger, Jerry Chun-Wei Lin, Quang-Huy Duong, Thu-Lan Dam, “PHM: Mining Periodic High-Utility Itemsets”, Industrial Conference on Data Mining, pp. 64-79, 2016. (ICDM 2016, LNCS, EI Best Paper Award Nomination)
21.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong, and Vincent S. Tseng, “Efficient Mining of Uncertain Data to Discover High-Utility Itemsets, “The International Conference on Web-Age Information Management, pp. 17-30, 2016. (WAIM 2016, LNCS, EI)
22.Wensheng Gan, Jerry Chun-Wei Lin*, Philippe Fournier-Viger, and Han-Chieh Chao, “More Efficient Algorithm for Mining Frequent Patterns with Multiple Minimum Supports,” The International Conference on Web-Age Information Management, pp. 3-16, 2016. (WAIM 2016, LNCS, EI)
23.Philippe Fournier-Viger, Jerry Chun-Wei Lin, Quang-Huy Duong, and Thu-Lan Dam, “FHM+: Faster High-Utility Itemset Mining using Length Upper-Bound Reduction,” International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems, pp. 115-127, 2016. (IEA/AIE 2016, LNCS, EI)
24.Philippe Fournier-Viger, Jerry Chun-Wei Lin, Tai Dinh and Hoai Bac Le, “Mining Correlated High-Utility Itemsets using the Bond Measure,” Hybrid Artificial Intelligence Systems, pp. pp 53-65, 2016. (HAIS 2016, LNCS, EI)
25.Lukas Orcik, Miroslav Voznak, Jan Rozhon, Filip Rezac, Jiri Slachta, Homero Toral-Cruz, and Jerry Chun-Wei Lin, “Prediction of Speech Quality Based on Resilient Backpropagation Artificial Neural Network,” International Conference on Communication, Management and Information Technology, 2016. (ICCMIT 2016, EI)
26.Jerry Chun-Wei Lin, Ting Li, Philippe Fournier-Viger, Tzung-Pei Hong, and Miroslav Voznak “Mining of High Average-Utility Itemsets without Candidate Generation,” International Conference on Communication, Management and Information Technology, 2016. (ICCMIT 2016, EI)
27.Philippe Fournier-Viger, Souleymane Zida, Jerry Chun-Wei Lin, Cheng-Wei Wu and Vincent S. Tseng, “Efficient Closed High-Utility Itemset Mining,” ACM/SIGAPP Symposium on Applied Computing, pp. 898-900, 2016. (ACM/SIGAPP SAC 2016, ACM, EI, Best Poster Award Nomination )
28.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, and Tzung-Pei Hong, “Efficient Algorithms for Mining Recent Weighted Frequent Itemsets in Temporal Transactional Databases,” ACM/SIGAPP Symposium on Applied Computing, pp. 861-866, 2016. (ACM/SIGAPP SAC 2016, ACM, EI)
29.Jerry Chun-Wei Lin, Xianbiao Lv, Philippe Fournier-Viger, Tsu-Yang Wu, and Tzung-Pei Hong, “Efficient Mining of Fuzzy Frequent Itemsets with Type-2 Membership Functions,” The Asian Conference on Intelligent Information and Database Systems, pp. 191-200, 2016. (ACIIDS 2016, LNCS, EI)
30.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, and Tzung-Pei Hong, “Mining Discriminative High Utility Patterns,” The Asian Conference on Intelligent Information and Database Systems, pp. 219-229, 2016. (ACIIDS 2016, LNCS, EI)
31.Souleymane Zida, Philippe Fournier-Viger, Cheng-Wei Wu, Jerry Chun-Wei Lin, and Vincent S. Tseng, “Efficient Mining of High-Utility Sequential Rules,” Machine Learning and Data Mining in Pattern Recognition, pp. 157-171, 2015. (MLDM 2015, LNCS, EI, Best Paper Award Nomination)
32.erry Chun-Wei Lin, Ting Li, Philippe Fournier-Viger, and Tzung-Pei Hong, “A Fast Algorithm for Mining Fuzzy Frequent Itemsets,” The International Conference on Fuzzy System and Data Mining, Vol. 29(6), pp. 2373-2379, 2015. (FSDM 2015)
33.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong, and Vincent S. Tseng, “Mining Potential High-Utility Itemsets over Uncertain Databases,” ASE BigData & SocialInformatics, Vol. 25, pp. 1-6, 2015. (ASE BD&SI 2015, ACM, EI)
34.Philippe Fournier-Viger, Jerry Chun-Wei Lin, and Prashant Barhate, “Efficient Incremental High Utility Itemset Mining,” ASE BigData & SocialInformatics, Vol. 53, pp. 1-6, 2015. (ASE BD&SI, ACM, EI)
35.Souleymane Zida, Philippe Fournier-Viger, Chun-Wei Lin, Cheng Wei Wu and Vincent S. Tseng, “EFIM: A highly efficient algorithm for high-utility itemset mining,” Mexican International Conference on Artificial Intelligence, pp. 530-546, 2015. (MICAI 2015, LNCS, EI)
36.Raïssa Yapan Dougnon, Philippe Fournier-Viger, Jerry Chun-Wei Lin and Roger Nkambou, “More Accurate User Profile Inference in Online Social Networks,” Mexican International Conference on Artificial Intelligence, pp. 84-99, 2015. (MICAI 2015, LNCS, EI)
37.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong, and Vincent S. Tseng, “Mining High-Utility Itemsets with Various Discount Strategies,” IEEE/ACM International Conference on Data Science and Advanced Analytics, pp. 1-10, 2015. (IEEE/ACM DSAA 2015, IEEE, EI)
38.Y. R. Dougnon, P. Fournier-Viger, Jerry Chun-Wei Lin, and R. Nkambou, “Accurate Online Social Network User Profiling,” German Conference on Artificial Intelligence, pp. 264-270, 2015. (KI 2015, LNCS, EI)
39.Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Jaroslav Frnda, Lukas Sevcik, Miroslav Voznak, “An Evolutionary Algorithm to Mine High-Utility Itemsets,” The Knowledge in Telecommunication Technologies and Optics, vol. 13(4), pp. 392-398, 2015. (KTTO 2015, EI)
40.Jerry Chun-Wei Lin, Qiankun Liu, Philippe Fournier-Viger, Tzung-Pei Hong, and Jeng-Shyang Pan, “A Swarm-based Sanitization Approach for Hiding Confidential Itemsets,” The International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 227-230, 2015. (IIHMSP 2015, EI)
41.Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Ming-Thai Wu, Tzung-Pei Hong, and Leon Shyue-Liang Wang, “A Swarm-based Approach to Mine High-Utility Itemsets,” The Multidisciplinary International Social Networks Conference, pp. 572-581, 2015. (MISNC 2015, EI)
42.Eric Ke Wang, Jerry Chun-Wei Lin, Tsu-Yang Wu, Chien-Ming Chen, and Yuming Ye, “Privacy Protection Framework in Social Networked Cars,” The Multidisciplinary International Social Networks Conference, pp. 553-561, 2015. (MISNC 2015, EI)
43.Jerry Chun-Wei Lin, Tsu-Yang Wu, Philippe Fournier-Viger, Guo Lin and Tzung-Pei Hong, “A Sanitization Approach of Privacy Preserving Utility Mining,” The International Conference on Genetic and Evolutionary Computing, pp. 47-57, 2015. (ICGEC 2015, Springer, EI, Best Paper Award)
44.Jaroslav Frnda, Miroslav Voznak, Martin Hlozak, Jiri Slachta, Jerry Chun-Wei Lin, “Application Tool for Prediction and Implementation of QoS in IP Based Network,” The Euro-China Conference on Intelligent Data Analysis and Applications, pp. 143-153, 2015. (ECC 2015, EI)
45.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, and Tzung-Pei Hong, “Mining Weighted Frequent Itemsets with the Recency Constraint,” The Asia-Pacific Web Conference, pp. 635-646, 2015. (APWeb 2015, LNCS, EI)
46.Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger and Tzung-Pei Hong, “Mining High-Utility Itemsets with Multiple Minimum Utility Thresholds,” The International C*Conference on Computer Science & Software Engineering, pp. 9-17, 2015. (C3S2E 2015, ACM, EI)
47.Jerry Chun-Wei Lin, Wensheng Gan, Tzung-Pei Hong, and Vincent S. Tseng, “HEWIM: High Expected Weighted Itemset Mining in Uncertain Databases,” The International Conference on Machine Learning and Cybernetics, pp. 439-444, 2015. (ICMLC 2015, EI)
48.Jerry Chun-Wei Lin, Wensheng Gan, and Tzung-Pei Hong, “A Fast Algorithm to Maintain the Discovered High-Utility Itemsets with Modified Records,” IEEE International Conference on System, Man, and Cybernetics, pp. 2573-2578, 2015. (IEEE SMC 2015, IEEE, EI)
59.Tsu-Yang Wu, Jeng-Shyang Pan, Chien-Ming Chen and Chun-Wei Lin, “Towards SQL Injection Attacks Detection Mechanism Using Parse Tree,” The International Conference on Genetic Evolutionary and Computing, pp. 371-380, 2015. (ICGEC 2015, EI)
任教和任导师经历    
哈尔滨工业大学 (深圳) 博士研究生 - 【协助指导】

[3] 甘文生 (2016/03-至今) 导师为赵涵捷特聘教授,研究领域:数据挖掘与大数据分析
# 学业:

[2] 陈 鹏 (2010/09-2015/10) 导师为潘正祥特聘教授,研究领域:数据挖掘的隐私保护
# 学业:5篇SCI期刊论文,5篇EI会议论文 (毕业去向:就职于国内某高校)

[1] 赵 鸣 (2011/02-2015/07) 导师为潘正祥特聘教授,研究领域:群体智能算法
# 学业:2篇SCI与2篇EI期刊论文,3篇EI会议论文 (毕业去向:就职于国内某高校)



哈尔滨工业大学 (深圳) 硕士研究生 - 【指导】

[8] 邵轶男 (2016/09-至今) 本科毕业于上海财经大学, 研究领域:数据挖掘与大数据分析
# 学业:

[7] 张瑜钰 (2016/09-至今) 本科毕业于合肥工业大学, 研究领域:数据挖掘的隐私保护
# 学业:

[6] 张杰雄 (2015/09-至今) 本科毕业于福州大学 (推免生), 研究领域:数据挖掘
# 学业:1篇EI会议论文, 哈尔滨工业大学特等奖学金等

[5] 任师峰 (2015/09-至今) 本科毕业于青岛理工大学, 研究领域:数据挖掘
# 学业:1篇SCI期刊论文,1篇EI会议论文

[4] 李 霆 (2014/09-2016/12) 本科毕业于西北工业大学, 研究领域:数据挖掘
# 学业:3篇SCI期刊论文,3篇EI会议论文 (毕业去向:华为深圳)

[3] 刘乾坤 (2014/09-2016/12) 本科毕业于辽宁科技大学, 研究领域:数据挖掘的隐私保护
# 学业:2篇SCI与1篇EI期刊论文,2篇EI会议论文 (毕业去向:华为深圳)

[2] 杨 璐 (2014/09-2016/12) 本科毕业于曲阜师范大学, 研究领域:数据挖掘与群体智能算法
# 学业:3篇SCI与1篇EI期刊论文,4篇EI会议论文 (毕业去向:百合音乐北京)

[1] 甘文生 (2013/09-2015/12) 本科毕业于华南师范大学 (推免生), 研究领域:数据挖掘
# 学业:10余篇SCI期刊论文,10余篇EI会议论文 (毕业去向:推荐攻博)
曾获哈工大第七届“十佳英才”提名奖,黑龙江省三好学生,哈工大优秀毕业生(金奖)、优秀毕业论文、三好学生和特等奖学金等



国立高雄大学 硕士研究生 - 【协助指导】

许宏全 (2011-2013) 研究领域:隐私保护数据挖掘
# 学业:SCI 期刊1篇,2篇会议论文 (台湾网路智能学会最佳硕士论奖)

林宗庆 (2009-2011) 研究领域:利用树状结构探勘完整语意项目集
# 学业:SCI 期刊3篇,会议论文5篇

张家境 (2009-2011) 研究领域:透过交易修改来隐藏敏感的频繁项目集
# 学业:1篇 EI期刊,2篇会议论文 (台湾网路智能学会最佳硕士论奖)

杨国栋 (2008-2010) 研究领域:应用于隐私保护数据探勘之启发性方法
# 学业:3篇SCI和1篇 EI期刊,4篇会议论文


国立中山大学 硕士研究生 - 【协助指导】

翁嘉蔚 (2010-2012) 研究领域:高效益数据挖掘与隐私保护
# 学业:3篇SCI和1篇 EI期刊,3篇会议论文


国立成功大学 硕士研究生 - 【协助指导】

陈欣怡 (2009-2011) 研究领域:准大快速循序样式树之维护
# 学业:1篇SCI期刊论文,4篇EI会议论文
全日制硕士课程 《物联网导论与应用》,32学时 (2014春, 2015春, 2015秋, 2016秋)
全日制本科课程 《计算机语言程序与设计》,48学时 (2015秋)
非全日制, 工程硕士课程 《物联网导论与应用》,32学时 (2016春)
非全日制, 工程硕士专题课 《工程硕士专题课》,4学时 (2015春, 2016春)
最后更新:2017-02