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师资队伍

周绮凤
职称:教授

研究方向::数据挖掘 信息检索 人工智能

办公室

邮箱:邮箱:zhouqf@xmu.edu.cn

主讲课程:

数据科学导论 (本科生)

C语言程序设计 (本科生)

模式识别(硕博研究生)


承担项目:

国家自然科学基金面上项目,基于社会化媒体大数据的事件知识优化表示和复杂关系表达研究,2022-2025,主持

福建省自然科学基金面上项目,基于大数据的灾难信息提取与挖掘研究, 2017-2020,主持

深圳市科技计划基础研究项目,基于时空大数据的突发事件中城市群体移动轨迹分析与预测, 2017-2019, 主持

国家自然科学基金青年项目,基于数据驱动的建筑环境影响评价关键问题研究, 2016-2018,主持

十三五空军预研项目,航空发动机典型气路故障智能诊断和预测技术,2020-2021,参与

整体包装解决方案系统,横向课题,2016-2017,主持。

有机产品全程追溯关键技术-企业端追溯子系统加工,横向课题,2015-2016,主持


代表性论文:

Chaojie An, Qifeng Zhou*, A reinforcement learning guided adaptive cost-sensitive feature acquisition method, Applied soft computing,2022(117).

Qifeng Zhou*, Xiangliu, Qing Wang, Interpretable Duplicate Question Detection Models Based on Attention Mechanism, Information Sciences, 2021.1(543): 259-272.

Qifeng Zhou*, Ruyuan Han, et.al. Joint prediction of time series data in inventory management, Knowledge and Information Systems, 2019, 61(2): 905-929.

Ruifeng Yuan, Qifeng Zhou*, Wubai Zhou. dTexSL: A dynamic disaster textual storyline generating framework. World Wide Web, 2019, 22(5): 1913-1933.

Ruifeng Yuan, Jinxin Ni, Qifeng Zhou*. Generating Multimedia Storyline for Effective Disaster Information Awareness. IEEE Access, 2019: 47401-47410.

Yang Fan, Li Tao, Zhou Qifeng*, Xiao Han. Cluster ensemble selection with constraints. Neurocomputing, 2017, 235: 59-70.

Qifeng Zhou, Hao Zhou, Tao Li, Cost-sensitive Feature Selection using Random Forest: Selecting Low-Cost Subsets of Informative Features. Knowledge-Based Systems, 95(2):1-11, 2016 (ESI Top 1%).

周绮凤,李涛,从政策驱动到技术践行:大数据开辟可持续发展研究新途径, 大数据,2016013-1.

Qifeng Zhou*, Hao Zhou, Qingqing Zhou, et.al, Structural damage detection based on posteriori probability support vector machine and Dempster–Shafer evidence theory. Applied Soft Computing, Volume 36:368-374, 2015.

Qifeng Zhou, Hao Zhou, Yongpeng Ning, Fan Yang*, Two Approaches for Novelty Detection using Random Forest. Expert Systems With Applications, 42(10):4840-4850, 2015.

Qifeng Zhou*, Hao Zhou, Yongpeng Ning, et.al, Structure Damage Detection Based on Random Forest Recursive Feature Elimination. Mechanical Systems and Signal Processing. 46(1):82-90, 2014.

Qifeng Zhou*, Yongpeng ning, Qingqing Zhou, Jiayan Lei, Structural Damage Detection Method Based on Random Forests and Data Fusion. Structural Health Monitoring, 12(1):48-58, 2013.