Qiannan Zhu

Qiannan Zhu

Lecturer in School of Artificial Intelligence, Beijing Normal University

个人简介

朱倩男 女 讲师 北京师范大学人工智能学院
电子邮箱：zhuqiannan@bnu.edu.cn

研究方向

研究方向为推荐系统，信息检索，知识表示与推理和大模型及其在教育领域的应用。

教育背景

  • 2021-2023，中国人民大学高瓴人工智能学院，博士后，导师：[窦志成]
  • 2018-2020，中科院信工所计算机系统结构专业，博士研究生，导师：[谭建龙]，指导老师：[周晓飞]
  • 2015-2018，中科院信工所计算机软件与理论专业，博士研究生，导师：[谭建龙]，指导老师：[周晓飞]

奖学金及荣誉称号

  • 2018年博士研究生国家奖学金
  • 2017年中国科学院大学“三好学生”
  • 2018年中国科学院信息工程研究所所长优秀奖

论文列表

  • Qiannan Zhu, Haobo Zhang, Qing He, Zhicheng Dou*. “Query-aware Explainable Product Search with Reinforcement Knowledge Graph Reasoning”. Accepted in IEEE Transactions on Knowledge and Data Engineering(TKDE 2023, first author, CCF-A).
  • Qingyu Bing, Qiannan Zhu, Zhicheng Dou*. “Cognition-aware Knowledge Graph Reasoning for Explainable Recommendation”. Accepted in the TheWebConf 2022 (WSDM 2023, Co first author, CCF-B).
  • Shuting Wang, Zhicheng Dou*, Jiongnan Liu, Qiannan Zhu, Jirong Wen. “Personalized and Diversified: Ranking Search Results in an Integrated Way”. Accepted in ACM Transactions on Information Systems,(TOIS 2023, CCF-A).
  • Qiannan Zhu, Haobo Zhang, Qing He, Zhicheng Dou*. “A Gain-Tuning Dynamic Negative Sampler for Recommendation”. Accepted in the TheWebConf 2022 (WWW 2022, first author, CCF-A).
  • Jianhuan Zhuo, Qiannan Zhu</b>, Yinliang Yue, Yuhong Zhao. “A Neighborhood-Attention Fine-grained Entity Typing for Knowledge Graph Completion”. Accepted in the 15th International Conference on Web Search and Data Mining (WSDM 2022, Corresponding author, CCF-B).
  • Jianhuan Zhuo, Qiannan Zhu*, Yinliang Yue, Yuhong Zhao, Weisi Han. “Learning Explicit User Interest Boundary for Recommendation”. Accepted in the TheWebConf 2022 (WWW 2022, Co first author, CCF-A).
  • Haonan Chen, Zhicheng Dou*, Qiannan Zhu, Xiaochen Zuo. “Integrating Representation and Interaction for Context-aware Document Ranking”. Accepted in IEEE Transactions on Knowledge and Data Engineering(TKDE 2022, CCF-A).
  • Ren Li, Yanan Cao, Qiannan Zhu, Guanqun Bi, Fang Fang, Yi Liu, Qian Li. “How Does Knowledge Graph Embedding Extrapolate to Unseen Data: a Semantic Evidence Views”. Accepted in the 36th AAAI Conference on Artificial Intelligence (AAAI 2022, CCF-A).
  • Jiongnan Liu, Zhicheng Dou*, Qiannan Zhu, Ji-Rong Wen . “A Category-aware Multi-interest Model for Personalized Product Search”. Accepted in in the TheWebConf 2022 (WWW 2022, CCF-A).
  • Xiaofei Zhou, Lingfeng Niu, Qiannan Zhu, Xingquan Zhu, Ping Liu, Jianlong Tan, Li Guo. “Knowledge Graph Embedding by Double Limit Scoring Loss”. Accepted in IEEE Transactions on Knowledge and Data Engineering(TKDE 2021, CCF-A).
  • Qiannan Zhu, Xiaofei Zhou, Jia Wu, Jianlong Tan, Li Guo. “A Knowledge-Aware Reasoning Network for Recommendation”. Accepted in the 34th AAAI Conference on Artificial Intelligence (AAAI 2020, first author, CCF-A).
  • Yue Yuan, Xiaofei Zhou, Shirui Pan, Qiannan Zhu, Zeliang Song, Li Guo. “A Relation-Specific Attention Network for Joint Entity and Relation Extraction”. Accepted in the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020, CCF-A).
  • Qiannan Zhu, Xiaofei Zhou, Jianlong Tan, Li Guo. “Knowledge Base Reasoning with Convolutional-based Recurrent Neural Networks”. Accepted in IEEE Transactions on Knowledge and Data Engineering(IEEE TKDE 2019, first author, CCF-A).
  • Qiannan Zhu, Xiaofei Zhou, Jia Wu, Jianlong Tan, Li Guo. “Neighborhood-Aware Attentional Representation for Multilingual Knowledge Graphs”. Accepted in the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019, CCF-A).
  • Qiannan Zhu, Xiaofei Zhou, Zeliang Song, Jianlong Tan, Li Guo. “DAN:Deep Attention Neural Network for News Recommendation”. Accepted in Proceedings of the 33th AAAI Conference on Artificial Intelligence (AAAI 2019, first author, CCF-A).
  • Xiaofei Zhou, Qiannan Zhu, Ping Liu, Li Guo. “Learning Knowledge Embeddings by Combining Limit-based Scoring Loss”. Accepted in in the International Conference on Information and Knowledge Management (CIKM 2017, CCF-B ).
  • Qiannan Zhu, Xiaofei Zhou, Peng Zhang, Yong Shi. “A Neural Translating General Hyperplane for Knowledge Graph Embedding”. Published in Journal of Computational Sciences (30)2019 (JCS 2019, first author ).
  • Qiannan Zhu, Xiaofei Zhou, Yuwen Wu, Ping Liu, Li Guo. “Multilingual knowledge graph embeddings with neural networks”. Accepted in the International Conference on Data Service (first author).
  • Qiannan Zhu, Xiaofei Zhou, JianLong Tan, Ping Liu, Li Guo. “Learning knowledge graph embeddings via generalized hyperplanes”. Accepted in the International Conference on Computational Science (first author).