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

Master Students

  • Wei Huang
  • Xiaoqing Huang
  • Chengqiang Lu
  • Shiwei Tong
  • Fengyuan Yang
  • Yu Yin
  • Haoyu Han
  • Shuanghong Shen
  • Song Cheng
  • Fei Wang
  • Xin Wang
  • Jianfu Zhu

Graduated

  • Runze Wu
  • Yuping Liu
  • Tianyu Zhu
  • Yuying Chen
  • Zai Huang

Publications


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.
  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), Anchorage, Alaska, USA, accepted, 2019.
  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), Anchorage, Alaska, USA, accepted, 2019. [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), Honolulu, USA, accepted, 2019. [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), Beijing, China, November 3-7 2019, accepted.
  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), Beijing, China, November 3-7 2019, accepted.
  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), Beijing, China, November 3-7 2019, accepted.
  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), Beijing, China, 2019, accepted.
  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), Beijing, China, 2019, accepted.

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] [BibTeX]
  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] [BibTeX]
  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] [BibTeX]
  4. Qi Liu, Han Wu, Yuyang Ye, Dongfang Du, Chuanren Liu, Hongke Zhao. Patent Litigation Prediction: A Hybrid Modeling Approach. The 27th International Joint Conference on Artificial Intelligence (IJCAI’2018), accepted, 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] [BibTeX]
  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] [BibTeX]
  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. 面向个性化教育的大数据分析方法研究与应用. [PDF]

Datasets


Code