重庆大学信息物理社会可信服务计算教育部重点实验室

信息物理社会可信服务计算教育部重点实验室

KEY LABORATORY OF DEPENDABLE SERvICE COMPUTING IN cYBER PHYSICAL SOCIETY( CHONGQING UNIVERSITY) MINISTRY OF EDUCATION

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曾骏的个人主页

服务计算,推荐系统

曾骏

副教授,硕士生导师

基本信息



职称:副教授,硕士生导师

E-mail::zengjun@cqu.edu.cn
研究方向:服务计算,推荐系统

个人简介



曾骏,1984年生,中共党员,博士,副教授,硕士生导师,数据科学系副系主任,中国计算机学会高级会员。2013年获得日本九州大学信息智能工学专业博士学位。研究领域包括移动大数据分析,移动用户轨迹挖掘,服务推荐,机器学习,人工智能。作为项目负责人承担国家自然科学基金青年项目1项、重庆市面上项目1项、博士后基金项目一等资助1项、留学人员回国科研启动金项目1项,以主研身份参与多项国家重点研发计划项目、国家科技支撑计划项目、国家自然科学基金项目;发表学术论文20余篇。担任多个国际权威期刊和会议评审人。

主持科研项目



[1] 国家重点研发计划课题,2019YFB1706104,区域汽车产业生态圈网络协同制造共享云服务平台研发与应用示范,2020.1-2022.12,主持子课题,在研.

[2] 重庆市自然科学基金面上项目,cstc2020jcyj-msxmX0900,移动环境下融合多源语义轨迹的地点推荐方法研究,2020.7-2023.6,在研.

[3] 国家自然科学基金青年项目,61502062,移动环境下基于用户行为识别的情境感知服务推荐研究,2016.1-2018.12,已结题.

[4] 中国博士后科学基金资助项目一等资助,2014M560704,已结题.

[5] 教育部留学回国人员科研启动基金,49批,已结题.

[6] 中央高校基本科研业务经费,2015CDJXY,已结题.

编写教材



[1] 《基于DirectX 11的3D图形程序设计案例教程》,曾骏,高旻,熊庆宇,文俊浩,重庆大学出版社,2015年5月.

[2] 《软件工程实训项目案例IV》,文俊浩,曾骏,熊庆宇,雷跃明,谭会辛,喻国良,重庆大学出版社,2019年1月.

[3] 《软件工程实训项目案例III——C++程序设计篇》,熊庆宇,文俊浩,雷跃明,谭会辛,曾骏,杨正益,重庆大学出版社,2016年4月.

专利



1] 发明专利:曾骏、李烽、何欣、文俊浩、柳玲,基于用户偏好、社交信誉度和地理位置的兴趣点推荐方法,2017(已授权)

[2] 发明专利:曾骏,何欣,姚娟,于扬,文俊浩,一种基于骑行上下文信息的共享单车流量预测方法,(专利申请号:202010795874.6)

[3] 发明专利:曾骏,唐浩然,于扬,姚娟,一种基于神经网络和地理影响的兴趣点推荐方法,2020(专利申请号:202010309687.2)

[4] 发明专利:曾骏,唐浩然,于扬,姚娟,一种基于区域划分和上下文影响的兴趣点推荐方法,2020(专利申请号:202010148082.X)

[5] 发明专利:曾骏,陈金彬,吴维锡,吴智涵,一种实时人体运动姿势矫正方法及系统,2019(专利申请号:201910527018.X)

[6] 发明专利:曾骏,何欣,唐浩然,文俊浩,基于循环神经网络和注意力机制的下一个地点预测方法,2019(专利申请号:201910872506.4)

[7] 发明专利:曾骏、李英华、唐浩然、何欣,一种基于用户签到稀疏矩阵的深度学习兴趣点推荐方法,2019(专利申请号:2019103088661.1)

代表性论文



[1]Jun Zeng, Xin He, Haoran Tang and Junhao Wen, Predicting the next location: A self‐attention and recurrent neural network model with temporal context, Transaction on Emerging Telecommunications Technologies, 2020,DOI: 10.1002/ett.3898(SCI)

[2]Jun Zeng, Feng Li, Xin He and Junhao Wen, “Fused collaborative filtering with user preference, geographical and social influence for point of interest recommendation”, International Journal of Web Services Research, Vol.16(4), 2019,PP. 40-52. DOI: 10.4018/IJWSR.2019100103 (SCI)

[3]Jun Zeng, Xin He, Haoran Tang, Junhao Wen , “A next location predicting approach based on a recurrent neural network and self-attention”, Collaborative Computing: Networking, Applications and Worksharing - 15th EAI International Conference CollaborateCom 2019 COLLABORATECOM(2019), August 19- 22, 2019,London, United kingdom,2019: 309-322.(EI, CCF推荐会议)

[4] Jun Zeng,Haoran Tang,Yinghua Li and Xin He, “A deep learning model based on sparse matrix for point-of-interest recommendation”, 31st International Conference on Software Engineering and Knowledge Engineering (SEKE 2019), Lisbon, Portugal, July 10-12, 2019, pp. 379-384. DOI: 10.18293/SEKE2019-156 (EI, CCF推荐会议)

[5] Jun Zeng, Xin He, Feng Li, Yinghua Li, Junhao Wen and Wei Zhou, “A Point-of-Interest Recommendation Method Using User Similarity,” WEB INTELLIGENCE, 16(2), 105-112. 2018.DOI: 10.3233/WEB-180376 (CCF 推荐期刊)

[6] Jun Zeng, Xin He, Yingbo Wu and Sachio Hirokawa, “User behavior analysis of Location-based Social Network”, 7th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2018 (IIAI AAI ’18) , July 8, 2018 - July 13, 2018, Yonago, Japan, pp.21-25(EI会议)

[7]Jun Zeng, Feng Li, Junhao Wen and Yingbo Wu, “A Point of Interest Recommendation Approach by Fusing Geographical and Reputation Influence on Location Based Social Networks,” 3th International Conference on Collaborative Computing: Networking, Applications and Worksharing(CollaborateCom 2017), Vol. 252 , pp. 232-242, 2018 (EI,CCF推荐会议)

[8] Jun Zeng, Feng Li, Yinghua Li, Junhao Wen, Yingbo Wu. “Exploring the Influence of Contexts for Mobile Recommendation,” International Journal of Web Services Research, 14(4), 33-49, 2017, DOI: 10.4018/IJWSR.2017100102 (SCI)

[9] Jun Zeng, Yinghua Li, Feng Li, Junhao Wen and Sachio Hirokawa, “A Point-of-Interest Recommendation Method Using Location Similarity,”6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 (IIAI AAI ’17), July 9, 2017 - July 3, 2017, Hamamatsu, Shizuoka, Japan, pp. 436-440 , 2017(EI会议)

[10]Jun Zeng, Feng Li, Brendan Flanagan, and Sachio Hirokawa,“LTDE: A Layout Tree Based Approach for Deep Page Data Extraction,” IEICE TRANS. INF. & SYST, Vol.E100-D, No.2 pp.285 -293.2017 (SCI)

[11]Jun Zeng, Feng Li, Haiyang Liu, Junhao Wen and Sachio Hirokawa, “A Restaurant Recommender System Based on User Preference and Location in Mobile Environment,” Proc. 2016 IIAI Int’l Conf. on Advanced Applied Informatics (IIAI AAI ’16), July 2016, pp. 55-60, Kumamoto, Japan, 2016. (EI会议)

[12]Jun Zeng, Brendan Flanagan, Sachio Hirokawa, and Eisuke Ito,“A Web Page Segmentation Approach Using Visual Semantics,” IEICE TRANS. INF. & SYST, E97-D(2) pp.223-230. 2014. (SCI)