About


BASE Group is part of the Anhui Province Key Laboratory of Big Data Analysis and Application of School of Computer Science and Technology, University of Science and Technology of China (USTC). Our research mainly focuses on applying BigData and AI techniques to education and science. Some of the topics include: educational resource understanding, cognitive diagnosis and student modeling, personalized education services, etc.

Members


Faculty

PhD Students

  • Chao Wang
  • Han Wu
  • Wei Huang
  • Yu Yin
  • Xiaoqing Huang
  • Shiwei Tong
  • Shuanghong Shen
  • Fei Wang

Master Students

  • Haoyu Han
  • Song Cheng
  • Xin Wang
  • Jianfu Zhu
  • Haoyang Bi
  • Weibo Gao
  • Yin Gu
  • Xin Lin
  • Ye Liu
  • Yixiao Ma
  • Jinze Wu
  • Zaixi Zhang
  • Yuqiang Zhou
  • Jie Huang
  • Songtao Fang
  • Ye Huang
  • Liyang He
  • Zheng Zhang
  • Xiaonan Ceng
  • Hang Zhang
  • Ruixin Li
  • Changyang Wu
  • Jialun Zhai
  • Si Yang
  • Xiangzi Yang
  • Ming Chen
  • Jiayu Liu
  • Derong Xu
  • Ning Liu

Graduated

  • Runze Wu
  • Yuping Liu
  • Tianyu Zhu
  • Yuying Chen
  • Zai Huang
  • Chengqiang Lu
  • Fengyuan Yang

Publications


2021

  1. Qi Liu, Zhenya Huang, Yu Yin, Enhong Chen*, Hui Xiong, Yu Su, Guoping Hu, EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 33(1): 100-115, January, 2021. [PDF] [SLIDE] [CODE]
  2. Zhenya Huang, Xin Lin, Hao Wang, Qi Liu, Enhong Chen*, Jianhui Ma, Yu Su, Wei Tong, DisenQNet: Disentangled Representation Learning for Educational Questions, The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’2021), Virtual Conference, August 14-18, 2021. Accepted.
  3. Shuanghong Shen, Enhong Chen, Qi Liu, Zhenya Huang, Wei Huang, Yu Yin, Yu Su, Shijin Wang, Learning Process-consistent Knowledge Tracing, The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’2021), Virtual Conference, August 14-18, 2021. Accepted.
  4. Yuqiang Zhou, Qi Liu*, Jinze Wu, Fei Wang, Zhenya Huang, Wei Tong, Huixiong, Enhong Chen, Jianhui Ma, Modeling Context-aware Features for Cognitive Diagnosis in Student Learning, The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’2021), Virtual Conference, August 14-18, 2021. Accepted.
  5. Jinze Wu, Qi Liu*, Zhenya Huang, Yuting Ning, Hao Wang, Enhong Chen, Jinfeng Yi and Bowen Zhou, Hierarchical Personalized Federated Learning for User Modeling, The 30th International World Wide Web Conference (WWW’2021), Ljubljana, Slovenia, April 19-23 2021.
  6. Xin Lin, Zhenya Huang*, Hongke Zhao, Enhong Chen, Qi Liu, Hao Wang, Shijin Wang, HMS: A Hierarchical Solver with Dependency-Enhanced Understanding for Math Word Problem, The 35th AAAI Conference on Artificial Intelligence (AAAI’2021), Virtual Conference, February 2-9, 2021. Accepted.
  7. Yin Gu, Qi Liu*, Kai Zhang, Zhenya Huang, Runze Wu, Jianrong Tao, NeuralAC: Learning Cooperation and Competition Effects for Match Outcome Prediction, The 35th AAAI Conference on Artificial Intelligence (AAAI’2021), Virtual Conference, February 2-9, 2021. Accepted.
  8. Weibo Gao, Qi Liu*, Zhenya Huang, Yu Yin, Haoyang Bi, Mu Chun Wang, Jianhui Ma, Shijin Wang, Yu Su, RCD: Relation Map Driven Cognitive Diagnosis for Intelligent Education Systems, The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’2021), Virtual Conference, July 11-15, 2021. Accepted.
  9. Yixiao Ma, Shiwei Tong, Ye Liu, Likang Wu, Qi Liu, Enhong Chen*, Wei Tong and Zi Yan, Enhanced Representation Learning for Examination Papers with Hierarchical Document Structure. The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’2021), Virtual Conference, July 11-15, 2021. Accepted.
  10. Shiwei Tong, Qi Liu*, Runlong Yu, Wei Huang, Zhenya Huang, Zachary A. Pardos, Weijie Jiang, Item Response Ranking for Cognitive Diagnosis. The 30th International Joint Conference on Artificial Intelligence (IJCAI’2021), Virtual Conference, August 21-26, 2021. Accepted.
  11. Songtao Fang, Zhenya Huang*, Ming He, Shiwei Tong, Xiaoqing Huang, Ye Liu, Jie Huang, QiLiu, Guided Attention Network for Concept Extraction. The 30th International Joint Conference on Artificial Intelligence (IJCAI’2021), Virtual Conference, August 21-26, 2021. Accepted.
  12. Jinze Wu, Zhenya Huang, Qi Liu*, Defu Lian, Hao Wang, Enhong Chen, Haiping Ma and Shijin Wang, Federated Deep Knowledge Tracing, The 14th ACM Conference on Web Search and Data Mining (WSDM’2021), Jerusalem, Israel, March 8-12 2021. accepted.

2020

  1. Zhenya Huang, Qi Liu, Yuying Chen, Le Wu, Keli Xiao, Enhong Chen*, Haiping Ma, Guoping Hu, Learning or Forgetting? A Dynamic Approach for Tracking the Knowledge Proficiency of Students, ACM Transactions on Information Systems (ACM TOIS), 38(2), Article 19, February 2020. [PDF] [SLIDE]
  2. Zhongkai Hao, Chengqiang Lu, Zhenya Huang, Hao Wang, Zheyuan Hu, Qi Liu*, Enhong Chen and Cheekong Lee, ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction, The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’2020): 731-739, San Diego, CA, USA, August 23-27 2020. [PDF] [SLIDE] [CODE]
  3. Zhenya Huang, Qi Liu, Weibo Gao, Jinze Wu, Yu Yin, Hao Wang and Enhong Chen*, Neural Mathematical Solver with Enhanced Formula Structure, The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’2020): 1729-1732, Xi’an, China, July 25-30, 2020. [PDF] [SLIDE]
  4. Shuanghong Shen, Qi Liu, Enhong Chen*, Han Wu, Zhenya Huang, Weihao Zhao, Yu Su, Haiping Ma and Shijin Wang, Convolutional Knowledge Tracing: Modeling Individualization in Student Learning Process, The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’2020): 1857-1860, Xi’an, China, July 25-30, 2020. [PDF] [SLIDE]
  5. Chao Wang, Hengshu Zhu*, Chen Zhu, Xi Zhang, Enhong Chen, and Hui Xiong*. Personalized Employee Training Course Recommendation with Career Development Awareness. In Proceedings of the 27th World Wide Web Conference (WWW’2020): 1648-1659, Taipei, China, April 2020. [PDF]
  6. Xin Wang, Wei Huang, Qi Liu*, Yu Yin, Zhenya Huang, Le Wu, Jianhui Ma, Xue Wang, Fine-Grained Similarity Measurement between Educational Videos and Exercises, The 28th ACM International Conference on Multimedia (ACM MM’2020), Seattle, USA, October 12-16 2020. [PDF]
  7. Fei Wang, Qi Liu*, Enhong Chen*, Zhenya Huang, Yuying Chen, Yu Yin, Zai Huang, Shijin Wang, Neural Cognitive Diagnosis for Intelligent Education Systems, The 34th AAAI Conference on Artificial Intelligence (AAAI’2020): 6153-6161, New York, USA, February 7-12 2020. [PDF] [Code]
  8. Haoyang Bi, Haiping Ma, Zhenya Huang*, Yu Yin, Qi Liu, Enhong Chen, Yu Su, and Shijin Wang, Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing, The 20th IEEE International Conference on Data Mining (ICDM’2020), Sorrento, Italy, November 17-20 2020. Accepted.
  9. Shiwei Tong, Qi Liu*, Wei Huang, Zhenya Huang, Enhong Chen, Chuanren Liu, Haiping Ma, and Shijin Wang, Structure-based Knowledge Tracing: An Influence Propagation View, The 20th IEEE International Conference on Data Mining (ICDM’2020), Sorrento, Italy, November 17-20 2020. Accepted.
  10. Ye Liu, Han Wu, Zhenya Huang, Hao Wang, Jianhui Ma, Qi Liu, Enhong Chen*, Hanqing Tao, and Ke Rui, Technical Phrase Extraction for Patent Mining: A Multi-level Approach, The 20th IEEE International Conference on Data Mining (ICDM’2020), Sorrento, Italy, November 17-20 2020. Accepted.
  11. Haoyu Han, Mengdi Zhang, Min Hou, Fuzheng Zhang, Zhongyuan Wang, Hongwei Wang, Enhong Chen, Jianhui Ma*, and Qi Liu, STGCN: A Spatial-Temporal Aware Graph Learning Method for POI Recommendation, The 20th IEEE International Conference on Data Mining (ICDM’2020), Sorrento, Italy, November 17-20 2020. Accepted.
  12. Wei Tong, Shiwei Tong, Wei Huang, Liyang He, Jianhui Ma*, Qi Liu, and Enhong Chen, Exploiting Knowledge Hierarchy for Finding Similar Exercises in Online Education Systems, The 20th IEEE International Conference on Data Mining (ICDM 2020), Sorrento, Italy, November 17-20, 2020. Accepted.

2019

  1. Qi Liu, Zhenya Huang, Yu Yin, Enhong Chen*, Hui Xiong, Yu Su, Guoping Hu. EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), accepted, 2019. [PDF]
  2. Qi Liu, Shiwei Tong, Chuanren Liu, Hongke Zhao, Enhong Chen*, Haiping Ma and Shijin Wang. Exploiting Cognitive Structure for Adaptive Learning. The 25nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’2019), 627-635, Anchorage, Alaska, USA, 2019. [PDF]
  3. Yu Yin, Qi Liu, Zhenya Huang, Enhong Chen*, Wei Tong, Shijin Wang and Yu Su. QuesNet: A Unified Representation for Heterogeneous Test Questions. The 25nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’2019), 1328-1336, Anchorage, Alaska, USA, 2019. [PDF] [Code]
  4. Chengqiang Lu, Qi Liu*, Chao Wang, Zhenya Huang, Peize Lin, Lixin He. Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective. The 33rd AAAI Conference on Artificial Intelligence (AAAI’2019), 1052-1060, Honolulu, USA, 2019. [PDF] [Code]
  5. Zhenya Huang, Qi Liu, Chengxiang Zhai*, Yu Yin, Enhong Chen*, Weibo Gao, Guoping Hu. Exploring Multi-Objective Exercise Recommendations in Online Education Systems. The 28th ACM International Conference on Information and Knowledge Management (CIKM’2019), 1261-1270, Beijing, China, November 3-7 2019. [PDF]
  6. Wei Huang, Qi Liu, Enhong Chen*, Yuying Chen, Zai Huang, Yang Liu, Dan Zhang, Zhou Zhao. Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach. The 28th ACM International Conference on Information and Knowledge Management(CIKM’2019), 1051-1060, Beijing, China, November 3-7 2019. [PDF]
  7. Song Cheng, Qi Liu*, Enhong Chen, Zai Huang, Zhenya Huang, Yuying Chen, Haiping Ma and Guoping Hu. DIRT: Deep Learning Enhanced Item Response Theory for Cognitive Diagnosis. The 25th ACM International Conference on Information and Knowledge Management (CIKM’2019), 2397-2400, Beijing, China, November 3-7 2019. [PDF]
  8. Han Wu, Kun Zhang, Guangyi Lv, Qi Liu, Runlong Yu, Weihao Zhao, Enhong Chen*, Jianhui Ma. Deep Technology Tracing for High-tech Companies. The 19th International Conference on Data Mining (ICDM’2019), 1396-1401, Beijing, China, 2019. [PDF]
  9. Xiaoqing Huang, Qi Liu*, Chao Wang, Haoyu Han, Jianhui Ma, Enhong Chen, Yu Su, Shijin Wang. Constructing Educational Concept Maps with Multiple Relationships from Multi-source Data. The 19th International Conference on Data Mining (ICDM’2019), 1108-1113, Beijing, China, 2019. [PDF]

2018

  1. Qi Liu, Runze Wu, Enhong Chen, Guandong Xu, Yu Su, Zhigang Chen, Guoping Hu. Fuzzy Cognitive Diagnosis for Modelling Examinee Performance. ACM Transactions on Intelligent Systems and Technology (ACM TIST), 9(4): 48, February 2018. [PDF]
  2. Qi Liu, Zai Huang, Zhenya Huang, Chuanren Liu, Enhong Chen*, Yu Su, Guoping Hu. Finding Similar Exercises in Online Education Systems. The 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’2018): 1821-1830, London, UK, August 19-23 2018. [PDF]
  3. Yu Yin, Zhenya Huang, Enhong Chen*, Qi Liu, Fuzheng Zhang, Xing Xie, Guoping Hu. Transcribing Content from Structural Images with Spotlight Mechanism. The 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’2018): 2643-2652, London, UK, August 19-23 2018. [PDF]
  4. Qi Liu, Han Wu, Yuyang Ye, Hongke Zhao*, Chuanren Liu, Dongfang Du. Patent Litigation Prediction: A Convolutional Tensor Factorization Approach. The 27th International Joint Conference on Artificial Intelligence (IJCAI’2018), 5052-5059, 2018. [PDF]
  5. Yu Su, Qingwen Liu, Qi Liu*, Zhenya Huang, Yu Yin, Enhong Chen, Chris Ding, Si Wei, Guoping Hu. Exercise-Enhanced Sequential Modeling for Student Performance Prediction. The 32nd AAAI Conference on Artificial Intelligence (AAAI’2018): 2435-2443, New Orleans, Louisiana, USA, February 2-7 2018. [PDF]
  6. Tianyu Zhu, Qi Liu, Zhenya Huang, Enhong Chen*, Defu Lian, Yu Su, Guoping Hu. MT-MCD: A Multi-task Cognitive Diagnosis Framework for Student Assessment. The 23rd International Conference on Database Systems for Advanced Applications (DASFAA’2018): 318-335, Gold Coast Australia, May 21-24 2018. [PDF]
  7. 王超, 刘淇, 陈恩红, 黄振亚, 朱天宇, 苏喻, 胡国平. 面向大规模认知诊断的 DINA 模型快速计算方法研究. 电子学报, 46(5):1047-1055, 2018年5月. [PDF]
  8. 刘淇, 陈恩红, 朱天宇, 黄振亚, 吴润泽, 苏喻, 胡国平. 面向在线智慧学习的教育数据挖掘技术研究. 模式识别与人工智能, 2018, 31(1): 77-90. [link]

2017

  1. Zhenya Huang, Qi Liu*, Enhong Chen, Hongke Zhao, Mingyong Gao, Si Wei, Yu Su, Guoping Hu. Question Difficulty Prediction for READING Problems in Standard Tests. The 31st AAAI Conference on Artificial Intelligence (AAAI’2017): 1352-1359, San Francisco, California USA, February 4-9, 2017. [PDF]
  2. Runze Wu, Guandong Xu*, Enhong Chen*, Qi Liu, Wan Ng. Knowledge or Gaming? Cognitive Modelling Based on Multiple-Attempt Response. The 26th International World Wide Web Conference (WWW’2017 Companion): 321-329, Perth, Australia, April 3-7, 2017. [PDF]
  3. Yuying Chen, Qi Liu, Zhenya Huang, Le Wu, Enhong Chen*, Runze Wu, Yu Su, Guoping Hu. Tracking knowledge Proficiency of Students with Educational Priors. The 26th ACM International Conference on Information and Knowledge Management (CIKM’2017), 989-998, Singapore, November 6-10, 2017. [PDF]
  4. Zai Huang, Zhen Pan, Qi Liu*, Bai Long, Haiping Ma, Enhong Chen. An Ad CTR Prediction Method Based on Feature Learning of Deep and Shallow Layers. The 26th ACM International Conference on Information and Knowledge Management (CIKM’2017), 2119-2122, Singapore, November 6-10, 2017. [PDF]
  5. 朱天宇,黄振亚,陈恩红*,刘淇,吴润泽,吴乐,苏喻,陈志刚,胡国平. 基于认知诊断的个性化试题推荐方法. 计算机学报,40(1): 176-191,2017年1月. [PDF]
  6. 刘淇, 陈恩红, 黄振亚, 苏喻, 胡国平. 面向个性化学习的学生认知能力分析. 中国计算机学会通讯, 13(4), 2017年4月. [link]

2016

  1. Yuping Liu, Qi Liu, Runze Wu, Enhong Chen*, Yu Su, Zhigang Chen, Guoping Hu. Collaborative Learning Team Formation: A Cognitive Modeling Perspective. The 21st International Conference on Database Systems for Advanced Applications (DASFAA’2016): 383-400, Dallas, Texas, USA, April 16-19, 2016. [PDF]

2015

  1. Runze Wu, Qi Liu*, Yuping Liu, Enhong Chen, Yu Su, Zhigang Chen, Guoping Hu. Cognitive Modelling for Predicting Examinee Performance. The 24th International Joint Conference on Artificial Intelligence (IJCAI’2015): 1017-1024, Buenos Aires, Argentina, July 25-31, 2015. [PDF]
  2. 黄振亚, 苏喻, 吴润泽, 刘玉苹, 刘淇, 陈志刚, 胡国平. 一种面向教育评估的智能教育辅助平台. 中国科学技术大学学报,45 (10): 846-854, 2015年10月. [link]

Slides


  • 刘淇. 基于认知情境建模的自适应学习方法. [PDF]
  • 刘淇. 面向个性化教育的大数据分析方法研究与应用. [PDF]

Datasets


Code