董祥军
发布人:研究生处  作者:  发布时间:2018-11-07   浏览次数:620


  

  

姓名

董祥军

性别

出生年月

19685

籍贯

山东寿光

政治面貌

中共党员

学历、学位

研究生、博士

行政职务


专业技术职务

教授

专业

计算机应用技术

导师类别

博导

博导兼职单位

辽宁工程技术大学

电子邮箱

d-xj@163.com

个人简历:

  董祥军,教授,博士后,博士生导师,曾任齐鲁工业大学信息学院副院长、院长。山东省计算机学会理事,山东物联网协会教育专委会副会长,山东电子学会教育专委会副主任委员,ACM(中国)会员,中国指挥与控制学会认知与行为专委会会员。1990年取得山东轻工业学院电气技术专业学士学位,1999年取得山东工业大学计算机应用技术硕士学位,2005年取得北京理工大学计算机应用专业博士学位。2007.6-2009.6在北京理工大学管理与经济学院从事博士后研究,2009.8-2010.2悉尼科技大学访问学者。2001年评为副教授,2005年破格评为教授。主持国家自然科学基金面上项目1项、中国博士后基金项目1项、山东省自然科学基金项目2项、山东省中青年科学家奖励基金项目1项、山东省研究生教育创新计划项目1项、山东省教育厅科技计划项目1项、山东高校优秀中青年教师国外合作项目1项,主持横向课题8项,参与国家级、省级纵向课题等10余项,到位经费400余万元。长期从事数据挖掘方面的研究,在负关联规则、负序列模式方面取得了丰硕的研究成果,发表学术论文70多篇,其中SCIEI收录50多篇,获得山东省教育厅优秀科研成果奖三等奖2项。指导全日制硕士研究生20余人,其中5人考取了悉尼科技大学、北京理工大学、武汉大学、中国海洋大学、北京邮电大学的博士生。任国际著名期刊“IEEE Transactions on Knowledge Discovery and Engineering”、“IEEE Intelligent Systems”、“Knowledge based Systems”等的审稿人;任国际知名会议PAKDD2016PAKDD2011PAKDD2009RICAI2016~2012AusAI2008~2012ADMA2016ADMA2009~2006DMBiz2007Workshop-of PAKDD2007)的程序委员会委员。主要研究方向:数据挖掘技术、机器学习、人工智能、信息集成、数据仓库技术等。

研究方向:

数据挖掘技术、机器学习、人工智能、信息集成、数据仓库技术等。   

主要科研成果:

科研项目

1.国家自然基金面上项目“负序列模式挖掘关键技术及其在医保欺诈检测中的应用研究”(项目编号:71271125,2013.1-2016.12)

2.山东省自然科学基金项目“基于项缺失的负序列模式快速挖掘技术及筛选机制研究”(项目编号:ZR2018MF011,2018.3-2020.12

3.横向课题“数据处理及分析系统软件开发”(2018.6-2019.6

4..山东省自然科学基金项目“负序列模式关键技术的研究”(项目编号ZR2011FM028,2011.7-2014.7

5.山东省自然科学基金项目“多数据库间的负关联规则挖掘技术研究”(项目编号:Y2007G25,已结题)

6.山东省中青年科学家奖励基金项目“负关联规则关键技术的研究”(项目编号:2006BS01017,已鉴定结题,国际先进水平)

7.中国博士后科学基金项目面上项目“非频繁项集挖掘及冗余规则修剪技术”(项目编号:20070420302,已结题)

8.山东省研究生教育创新计划项目“IT研究生RAI培养模式的研究”(项目编号SDYY09037,已结题)

9.山东省教育厅科技计划项目“水库大坝信息集成与智能决策系统”(项目编号:J06N06, 已鉴定结题,国际先进水平)

10.山东省教育厅“山东高校优秀中青年教师国外合作项目”

11.企业合作项目“污水处理厂自动化控制系统(290万元)”、“西苇水库大坝信息集成与智能决策系统(41万元)”,“峡山/白浪河水库大坝渗流信息集成与智能决策系统”(14.7万元/12.2万元)等企业合作项目

12.山东省高等学校科技计划项目“基于重复序列的负序列模式挖掘关键技术的研究” (第2位,项目编号J12LN10,已结题)

13.山东省自然科学基金项目“加权负序列模式挖掘技术的研究” (5位,项目编号ZR2012FM032,已结题)

14.山东省自然科学基金项目 “加权负关联规则挖掘技术的研究”(2位,项目编号Y2008G26,已结题)

15.济南市青年科技明星计划项目“Web用户正负加权频繁遍历访问模式挖掘关键技术研究”(第2位,项目编号JN20090202,已结题)

论文

  1. Longbing Cao, Xiangjun Dong, Zhigang Zheng. e-NSP: Efficient Negative Sequential Pattern Mining. Artificial Intelligence, 2016, 235: 156-182(CCF推荐A类期刊,SCI二区, IF=3.333)

  2. Can Wang, Xiangjun Dong, Fei Zhou, et al. Coupled Attribute Similarity Learning on Categorical Data, in IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 4, pp. 781-797, April 2015. (CCF推荐B类期刊,SCI一区, IF=4.854)

  3. Qian Gao, Deqian Fu, Xiangjun Dong. A Context-Aware Mobile User Behavior-Based Neighbor Finding Approach for Preference Profile Construction. Sensors, 2016, 16(8). (SCI二区, IF=2.033)

  4. Xiangjun Dong, Zhigang Zheng, Longbing Cao, et al. e-NSP: Efficient Negative Sequential Pattern Mining Based on Identified Positive Patterns Without Database Rescanning. Proceedings of 19th Association of Computing Machinery Conference on Information and Knowledge Management, Glasgow, CIKM2011国际知名会议CCF-B: 825-830

  5. Jialun Pei, Long Zhao, Xiangjun Dong*, et al. Effective algorithm for determining the number of clusters and its application in image segmentation. Cluster Computing, 2017(3):1-10. (SCI三区, IF=2.040)

  6. Long Zhao, Qian Gao, Xiangjun Dong*, et al. K- local maximum margin feature extraction algorithm for churn prediction in telecom. Cluster Computing, 2017, 20(2):1401-1409. (SCI三区, IF=2.040)

  7. Tiantian Xu, Jianliang Xu, Xiangjun Dong*. Mining High Utility Sequential Patterns Using Multiple Minimum Utility[J]. International Journal of Pattern Recognition & Artificial Intelligence, 2018, 32(6).

  8. Jialun Pei, Weiyang Chen, Xiangjun Dong, Magnetic Resonance Imaging Brain Image Segmentation Method Based on Adaptive Clustering Algorithm, Journal of Medical Imaging and Health Informatics, 2017,7:1-7(SCI四区, IF=0.621)

  9. Long Zhao, Linfeng Jiang, Xiangjun Dong*. Supervised feature selection method via potential value estimation. Cluster Computing, 2016:1-11. (SCI三区, IF=1.514,)

  10. Long ZhaoXue DongWeiYang ChenLinFeng JiangXiangJun Dong*. The combined cloud model for edge detection. Multimedia Tools and Applications, 2017, 76(13):15007-15026. (SCI四区, IF=1.530)

  11. Yongshun Gong, Tiantian Xu, Xiangjun Dong*, et al. e-NSPFI: Efficient Mining Negative Sequential Pattern from Both Frequent and Infrequent Positive Sequential Patterns. International Journal of Pattern Recognition and Artificial Intelligence, Volume 31, Issue 02, 2017. (SCI四区, IF=0.915)

  12. Tiantian Xu, Xiangjun Dong*, Jianliang Xu et al. E-msNSP: Efficient negative sequential patterns mining based on multiple minimum supports. International Journal of Pattern Recognition and Artificial Intelligence, Volume 31, Issue 02, 2017. (SCI四区, IF=0.915)

  13. Chuanlu Liu, Guohua Lv, Xiangjun Dong *. Selecting Actionable Patterns from Positive and Negative Sequential Patterns. Journal of Residuals Science & Technology, Vol. 14, No. 1, January 2017. 

  14. TianTian Xu, Longbing Cao, Xiangjun Dong et al. Mining High Utility Sequential Patterns with Negative Item Values. International Journal of Pattern Recognition and Artificial Intelligence, 2017. (SCI四区, IF=0.915)

  15. Ping QiuLong ZhaoXiangjun Dong*NegI-NSP: Negative Sequential Pattern Mining based on loose constraintsIECON 2017.(EI已录用)

  16. Tongxuan Li, Tiantian Xu, Xiangjun Dong*, HUNSPM: An Efficient Algorithm for Mining High Utility Negative Sequential Patterns, ICNC-FSKD 2017.(EI已录用)

  17. Chenlu Li, , Xiangjun Dong*,Xue Dong et al. FP-Growth Based Method for Mining Infrequent and Frequent Itemsets with 2-Level Minimum Support, ICNC-FSKD 2017.(EI已录用)

  18.Xiangjun Dong, Fengrong SunXiqing Han and Ruilian Hou. Study of Positive and Negative Association Rules based on Multi-confidence and Chi-squared testADMA06Springer Lecture Notes in Computer Science 4093Springer-Verlag Berlin Heidelberg 2006 ,pp.100-109 (SCIIF=0.402), 2006.

  19. Yongshun Gong, Chuanlu Liu, Xiangjun Dong*. Research on Typical Algorithms in Negative Sequential Pattern Mining. Open Automation & Control Systems Journal, 2015, 7(1):934-941. (EI)

  20. Xiangjun Dong, Chuanlu Liu. Mining interesting infrequent and frequent itemsets based on multiple level minimum supports and minimum correlation strength. International Journal of Services Technology and Management2015, 21(4/5/6). (EI)

  21. Xiangjun Dong, Tiantian Xu, Yuanyuan Xu, et al. E-msNFIS: An Efficient Method for Mining Negative Frequent Itemsets based on Multiple Minimum Supports. Open Cybernetics & Systemics Journal, 2015, 9(1):428-432.(EI)

  22. Xiangjun Dong: Mining Interesting Infrequent and Frequent Itemsets Based on Minimum Correlation Strength. In Proc. of 3rd International Conference on Artificial Intelligence and Computational Intelligence, AICI 2011, Taiyuan, China, Part I (AICI (1) 2011). Lecture Notes in Computer Science 7002 Springer 2011, pp.437-443, September 24-25, 2011

  23. Xiangjun Dong, Liang Ma, He Jiang. e-NFIS: Efficient negative frequent itemsets mining only based on positive ones. In Proc. of 2011 IEEE 3rd International Conference on Communication Software and Networks (ICCSN2011), pp.517-519 (EI) ,May. 2011

  24. Xiangjun Dong, Shiju Shang, Jie Li, He Jiang. Mining global exceptional rules in multi-database. 2009 International Forum on Information Technology and Applications, IFITA 2009, v 2, pp. 680-683 , 2009 .(EIAccession number: 20094512431030)

  25. Xiangjun Dong, Shiju Shang, Jie Li, He Jiang. Application of negative association rules in multi-database. 2008 International Symposium on Information Science and Engineering, ISISE 2008, v 1, pp. 460-463, 2008, (EIAccession number: 20091311977685)

  26. Xiangjun Dong, Zhendong Niu, Xuelin Shi, Xiaodan Zhang, Donghua Zhu. Mining both Positive and Negative Association Rules from Frequent and Infrequent Itemsets. IN proceedings of ADMA07, Harbin, China, 2007, LNAI 4632, Springer-Verlag Berlin Heidelberg, pp.122-133 2007 .(EIAccession number: 080311023324)

  27. Xiangjun Dong, Zhiyun Zheng, Zhendong Niu, Qiuting Jia. Mining Infrequent Itemsets based on Multiple Level Minimum Supports, The Second International Conference on Innovative Computing, Information and Control (ICICIC2007), September 5 - 7, 2007, Japan, (EI)

  28. Xiangjun Dong, Gang Li, Hongguo Wang, Yuebin Guo, and Yueyue Yang. Mining Infrequent Itemsets based on Extended MMS Model. Third International Conference on Intelligent Computing, ICIC07, CCIS 2, pp. 190–198, 2007. Springer-Verlag Berlin Heidelberg 2007 (ISTP)

  29. Xiangjun Dong, Zhendong Niu, Donghua Zhu, Zhiyun Zheng, and Qiuting Jia. Mining Interesting Infrequent and frequent Itemsets based on MLMS Model. The Fourth International Conference on Advanced Data Mining And Applications, Chengdu, China (ADMA2008), LNAI 5139, Springer-Verlag Berlin Heidelberg, pp. 444-451 ,October, 2008 (EI)

  30. Yang Bin, Xiangjun Dong*, Fufu Shi. Research of WEB usage mining based on negative association rules. IFCSTA 2009 Proceedings - 2009 International Forum on Computer Science-Technology and Applications (IFCSTA2009), v1, p196-199, 2009 (EI Accession number: 20101312804863)

  31. Shiju Shang, Xiangjun Dong*, Runian Geng, Long Zhao. Mining Negative Association Rules in Multi-database. Fifth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD2008), Jinan, China,pp.596-599 ,Oct.2008 (EI, Accession number: 090211845665)

  32. Runian Geng, Xiangjun Dong, Jing Zhao, et al. WHFPMiner: efficient mining of weighted highly-correlated frequent patterns based on weighted FP-tree approach. LNCS,Vol.5264, pp.730-739 , 2009.EI, Access Number:20090611891651

  33. Runian Geng, Wenbo. Xu, Xiangjun Dong. Efficient mining of interesting weighted patterns from directed graph traversals. Journal of Integrated Computer-Aided Engineering,.16(1),pp.21-49,2009.SCI四区)

  34. Long Zhao, Xiangjun Dong, Shiju Shang. The present situation and development tendency of Classification Based on negative association rules. In: W. Xu, D. Liu, eds. Proc. of the 7th International Symposium on Distributed Computing and Applications for Business Engineering and Science(DCABES’08). Beijing: Publishing House of Electronics Industry,2008.(ISTP)

  35. Sun, Feng-Rong, Liu, Ze; Dong, Xiang-Jun. Surface reconstruction of the coronary arterial walls from intravascular ultrasound images. Journal of Electronic Imaging, v 16, n 4, 2007, p 043016 (SCI, IF=0.7)

  36. Youbo Wang, Xiangjun Dong, Zhiguang Tian. FPGA Based Design of Elliptic Curve Cryptography Coprocessor. In Proceedings of the 3rd International Conference on Natural Computation (ICNC 2007) Vol IV, Haikou, China, 2007.9, IEEE Press (EI)

  37. Jianbin Chen, Xiangjun Dong, Hantao Song. The Refinement Algorithm Consideration in Text Clustering Scheme Based on Multilevel Graph. Wuhan University Journal of Natural Sciences, 2004.9 (EI)

  38. Zhengyu Wu, Xiangjun Dong, Hantao Song. Ant-based Energy Aware Disjoint Multipath Routing Algorithm in MANETs. The First International Symposium on Pervasive Computing and applications (SPCA06) 2006, China IEEE Press  (EI)

  39. Runian Geng, Wenbo Xu, and Xiangjun Dong: Efficient mining of interesting weighted patterns from directed graph traversals [J]. Journal of Integrated Computer-Aided Engineering, 2008.15(4)SCI

  40. GENG Ru-nian, DONG Xiang-jun, XU Wen-bo.Weighted frequent patterns mining algorithm based on global graph traversals. Computer Integrated Manufacturing Systems, vol 6,2008. p1220—1229 Language: Chinese

  41. Xuelin Shi, Ying Zhao, Xiangjun Dong. Web Page Categorization Based on K-nn and Svm Hybrid Pattern Recognition Algorithm. WCCI2008 (EI)

  42. Jiang, He, Luan, Xiumei, Dong, Xiangjun. Mining weighted negative association rules from infrequent itemsets based on multiple supports. 2012 International Conference on Industrial Control and Electronics Engineering, ICICEE 2012, 2012/8/23-2012/8/25, pp 89-92, Xi'an,,2012. (EI )

  43. Runian Geng, Xiangjun Dong, Jing Zhao, and Wenbo Xu: WHFPMiner: efficient mining of weighted highly-correlated frequent patterns based on weighted FP-tree approach[C].In: Proc. of the 5th International Symposium on Neural Networks (ISNN’08). LNCS, Heidelberg: Springer Verlag, 2008 EI

  44. Runian Geng, Xiangjun Dong, He Jiang, and Wenbo Xu: WTSPMiner: efficiently mining weighted sequential patterns from directed graph traversals[C].In: Proc. of the 4th International Conference on Intelligent Computing (ICIC'08). LNCS, Heidelberg: Springer Verlag, 2008, Volume 5226, pp.398-405. EI

  45. Runian Geng, Xiangjun Dong, Ping Zhang, and Wenbo Xu: WTMaxMiner: Efficient Mining of Maximal Frequent Patterns Based on Weighted Directed Graph Traversals[C].In: Proc. of the 3rd IEEE International Conference on Cybernetics and Intelligent Systems (CIS’08). Washington: IEEE Computer Society, Sep. 2008EI

  46. Runian Geng, Xiangjun Dong, Guoling Liu, and Wenbo Xu: Efficiently mining maximal frequent patterns from traversals on weighted directed graph using statistical theory[C].In: Proc. of the 5th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'08). Washington: IEEE Computer Society, Aug. 2008EI

专利

1.正负序列模式筛选方法在客户购买行为分析中的应用(申请号:201510025586.1

2.重复负序列模式在客户购买行为分析中的应用(申请号:201510025944.9

3.基于单项缺失的负序列模式在商品推荐中的应用(申请号:201710018624.x

4.Top-k可决策的负序列模式在客户投保行为分析中的应用(申请号:201710018623.5

5.非频繁序列中挖掘可决策负序列模式的购买行为分析方法(申请号:20170768749.4

6.一种基于选取合适聚类数目的聚类算法的数字图像处理方法(申请号201710018065.2

7.基于自适应聚类算法的核磁共振图像分割方法(申请号:201710769101.9

8.基于逻辑推理负关联规则修剪技术的客户购买行为分析方法(申请号:201710768728.2

9.二次相关判定法选取有效的负关联规则在客户购买行为分析中的应用(申请号:201510963625.2

10.快速的负序列挖掘模式在客户购买行为分析中的应用(申请号:201510026575.5

11.多支持度的正负序列模式在客户购买行为分析中的应用(申请号:201510026256.4

荣誉称号:

社会兼职:

  山东省计算机学会理事,山东物联网协会教育专委会副会长,山东电子学会教育专委会副主任委员,ACM(中国)会员,中国指挥与控制学会认知与行为专委会会员