Dr. Ritu Chaturvedi

University of Guelph

About

Dr. Ritu Chaturvedi

I am an Assistant Professor at SoCS, University of Guelph. My research interests include data mining and machine learning, with a focus on:

  • Educational data mining
  • Text mining

Teaching

Courses

  • Currently teaching (Fall 2022):
    • CIS1250 - Software Engineering I
    • CIS1300 - Programming
  • Previously taught:
    • CIS1200 - Introduction to Computing
    • CIS1500 - Introduction to Programming
    • CIS2500 - Intermediate Programming
    • CIS3530 - Data Base Systems and Concepts
    • CIS4900 - Computer Science Project

Research

Recent Publications

  1. Ritu Chaturvedi, Christie I. Ezeife, Customized Learning in Online Tutoring Systems by Mining Learning Units from Tasks and Examples, International Journal on Data Science and Technology. Volume 8, Issue 1, March 2022 , pp. 22-35. doi: 10.11648/j.ijdst.20220801.14
  2. C. I. Ezeife, M. Nasir, R. Chaturvedi and A. V. Castro, "The HSPRec E-Commerce System Open Source Code Implementation," 2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall), 2021, pp. 42-48, doi: 10.1109/ICISFall51598.2021.9627424.
  3. R. Chaturvedi and V. V. Patnaik, Intelligent Feature Selection on Multivariate Dataset using Advanced Data Profiling, 2022 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), 2022, pp. 1-7, doi: 10.1109/IEMTRONICS55184.2022.9795745.
  4. Ezeife, C. I., Aravindan, V., & Chaturvedi, R. (2020). Mining Integrated Sequential Patterns From Multiple Databases. International Journal of Data Warehousing and Mining (IJDWM), 16(1), 1-21.
  5. Nguyen, J., & Chaturvedi, R. Quarantine Quibbles: A Sentiment Analysis of COVID-19 Tweets. IEEE 11th Annual Information Technology, Electronics and Mobile Communication Conference (IEEE IEMCON 2020).
  6. Chaturvedi, R., & Ezeife, C. I., Clustering Examples in Web-based Tutoring Systems Based on Relevance of Concepts. The Fourth International Conference on Intelligent Computing in Data Sciences ICDS2020.
  7. Ejieh, C., Ezeife, C. I., & Chaturvedi, R. (2019, April). Mining product opinions with most frequent clusters of aspect terms. In Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing (pp. 546-549).
  8. Chaturvedi, R., Veerpal Brar., Jai Geelal,, Kevin Kong. Concept Extraction: A Modular Approach to Extraction of Source Code Concepts. In Computer and Information Technology (CIT), 2018 IEEE International Conference on (pp. 1860-1866). July 30th – Aug 3rd Halifax, Canada.
See Full List

Contact

(519)-824-4120 x 53986

Office: Reynolds Building 2211