刘辉林
-
教授
博士生导师
硕士生导师
- 教师英文名称:Huilin Liu
- 教师拼音名称:Liu Huilin
- 电子邮箱:91fed6c3e7042f31caffe63bba93c85e832dfba89079d7b03684830115de630ba3fc497724a0d73e4d5156991938454711c7b918e6c4a4e749ca72dbc7d03b7d125ee03a052aa004870cda75739b5c06e5099060176d59e16fcd6d70ab958b426d49d745db4bd8a8465567c963cdea3ca2070ce0c2aee859160fb4c70ef438eb
- 入职时间:1988-07-01
- 学历:博士研究生毕业
- 在职信息:在职
- 学科:计算机系统结构
计算机软件与理论
计算机应用技术
智能科学与技术
访问量:
-
陈忱,刘辉林,信俊昌,王国仁.基于区域子图的实体相关性度量[J].东北大学学报(自然科学版),2012,33(11):1551-1554..
-
Huilin Liu, Junchang Xin, Yuanyuan Yang, Dapeng Wang. A QoS Routing Scheme for Vehicle Wireless Communication Based on Improved Particle Swarm Optimization, ICFWI, 2011, 143, 539-547..
-
Chen Chen, Liu Huilin, Zhang Liwei. Discrimination of Person Names Based on Contexts Co-occurrence. FSKD, 2011, 2605-2609..
-
ChenChen, Wang Guoren, Liu huilin, XinJunchang. A New Framework for Searching the Informative Subgraph Based on PSO. CIKM, 2011, 453-462..
-
Chen C,Liu H,Zhang L.Discrimination of person names based on contexts co-occurrence.[C]// Eighth International Conference on Fuzzy Systems & Knowledge Discovery. IEEE, 2011..
-
Chen, Chen; Liu, Huilin; Wang, Guoren; Ding, Linlin; Yu, Lili, Entity relationship extraction based on potential relationship pattern, 2010 International Conference on Web Information Systems and Mining, WISM 2010, Sanya, China, 2010.10.23-2010.10.24.
-
Liu H L H , Li Z L Z , Xin J X J , et al. Dominating ranking algorithm for information retrieval[C]// Seventh International Conference on Fuzzy Systems & Knowledge Discovery. IEEE, 2010..
-
Liu H , Chen Z , Wang G , et al. A method of Grade division based on Set Pair Analysis.[C]// International Conference on Fuzzy Systems & Knowledge Discovery. IEEE, 2010..
-
Liu, Huilin; Chen, Chen; Zhang, Liwei; Wang, Guoren, The reaserch of lable-mapping-based entity attribute extraction, 2010 1st IEEE International Conference on Progress in Informatics and Computing, PIC 2010, Shanghai, China, 2010.12.10-2010.12.12.
-
Chen C C C , Liu H L H , Wang G W G , et al. A New Topic Filter Based on Maximum Entropy Model[C]// International Conference on Fuzzy Systems & Knowledge Discovery. IEEE, 2009..