Chase Geigle

Publications

Books

  1. ChengXiang Zhai and Chase Geigle. forthcoming. Statistical Language Models for Text Data Retrieval and Analysis.The Information Retrieval Series. Springer International Publishing, 1st edition, forthcoming.

Journal Articles

  1. Chase Geigle and ChengXiang Zhai. 2017. Modeling MOOC Student Behavior with Two-Layer Hidden Markov Models. Journal of Educational Data Mining, 9(1):1–24, September.

Book Chapters

  1. Chase Geigle, Qiaozhu Mei, and ChengXiang Zhai. 2018. Feature Engineering for Text Data. In Gouzhu Dong and Huan Liu, editors, Feature Engineering for Machine Learning and Data Analytics, Chapman & Hall/CRC Data Mining and Knowledge Discovery Series, pages 15–45. CRC Press, 1st edition, April.

Conference Articles

  1. Chase Geigle, Himel Dev, Hari Sundaram, and ChengXiang Zhai. 2019. A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms. In Proceedings of the 13th International Conference on Web and Social Media, to appear. AAAI, June.
  2. Chase Geigle, Ismini Lourentzou, Hari Sundaram, and ChengXiang Zhai. 2018. CLaDS: A Cloud-Based Virtual Lab for the Delivery of Scalable Hands-on Assignments for Practical Data Science Education. In Proceedings of the 23rd Annual Conference on Innovation and Technology in Computer Science Education, 176–181, New York, NY, USA, July. ACM.
  3. Fareedah ALSaad, Assma Boughoula, Chase Geigle, Hari Sundaram, and ChengXiang Zhai. 2018. Mining MOOC Lecture Transcripts to Construct Concept Dependency Graphs. In Proceedings of the Eleventh International Conference on Educational Data Mining, 467–473. IEDMS, July.
  4. Himel Dev, Chase Geigle, Qingtao Hu, Jiahui Zheng, and Hari Sundaram. 2018. The Size Conundrum: Why Online Knowledge Markets Can Fail at Scale. In Proceedings of WWW 2018: The Web Conference, 65–75, New York, NY, USA, April. ACM.
  5. Chase Geigle and ChengXiang Zhai. 2017. Modeling MOOC Student Behavior with Two-Layer Hidden Markov Models. In Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale, 205–208. ACM, April.
  6. Assma Boughoula, Chase Geigle, and ChengXiang Zhai. 2017. A Probabilistic Approach for Discovering Difficult Course Topics Using Clickstream Data. In Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale, 303–306. ACM, April.
  7. Sean Massung, Chase Geigle, and ChengXiang Zhai. 2016. MeTA: A Unified Toolkit for Text Retrieval and Analysis. In Proceedings of the 54th Annual Meeting of the Association for Computational Lingustics: System Demonstrations, 91–96, Berlin, Germany, August. ACL.
  8. Kenneth Heafield, Chase Geigle, Sean Massung, and Lane Schwartz. 2016. Normalized Log-Linear Language Model Interpolation is Efficient. In Proceedings of the 54th Annual Meeting of the Association for Computational Lingustics, 876–886, Berlin, Germany, August. ACL.
  9. Chase Geigle, ChengXiang Zhai, and Duncan Ferguson. 2016. An Exploration of Automated Grading of Complex Assignments. In Proceedings of the Third (2016) ACM Conference on Learning @ Scale, 351–360. ACM, April.
  10. Chase Geigle and ChengXiang Zhai. 2016. Scaling up Online Question Answering via Similar Question Retrieval. In Proceedings of the Third (2016) ACM Conference on Learning @ Scale, 257–260. ACM, April.
  11. Lane Schwartz, Bill Bryce, Chase Geigle, Sean Massung, Yisi Liu, Haoruo Peng, Vignesh Raja, Subhro Roy, and Shyam Upadhyay. 2015. The University of Illinois submission to the WMT 2015 Shared Translation Task. In Proceedings of the Tenth Workshop on Statistical Machine Translation, 192–198, Lisbon, Portugal, September. ACL.
  12. Swarup Kumar Sahoo, John Criswell, Chase Geigle, and Vikram Adve. 2013. Using Likely Invariants for Automated Software Fault Localization. In Proceedings of the Eighteenth International Conference on Architectural Support for Programming Languages and Operating Systems, 139–152, New York, NY, USA, March. ACM.