+966 13 849 9263
ralabdulrahman1@pmu.edu.sa
F-119
Dr. Rabaa Alabdulrahman is a Saudi national, working as an Assistant Professor at the department of Business Administration at PMU, KSA. She obtained her undergraduate degree in Computer & Information Systems from King Faisal University in Dammam, Saudi Arabia, in 2007. Her master’s degree in System Science from University of Ottawa in Ottawa, Canada, in 2014 and her Ph.D. in Digital Transformation and Innovation from University of Ottawa in Ottawa, Canada in 2020.
Her doctoral dissertation examines the use of machine learning to improve recommendation systems quality. In her research, she developed three frameworks, integrated design, and analysis environment for each methodology. Each framework has been published in conferences and is freely available to the community.
She has authored 4 conference papers, 2 book chapters, and 1 journal paper published in the International Joint Conference of Knowledge Discovery, Knowledge Engineering and Knowledge Management (KDIR), the Knowledge Discovery and Information Retrieval (CCIS) book, and the expert systems with applications journal. She has also served as a reviewer of journal articles.
Dr. Alabdulrahman’s primary research interests include e-commerce, recommendation systems, machine learning and business intelligence. As future research direction, Dr. Alabdulrahman aims to research the impact of digitalization on businesses. In recent years, KSA has exerted tremendous efforts in transforming to e-government, e-health, and e-commerce. Dr. Alabdulrahman believes there are many hidden gems yet to be researched and improved.
PhD In Digital Transformation and Innovation (DTI), university of ottawa, Canada
Thesis title: Towards Personalized Recommendation Systems: Domain-Driven Machine Learning Techniques and Frameworks.
Comprehensive exam in May 2016. Exam topic included the following: Data mining, data warehousing with focus on click stream analysis and viral marketing. Also, the topic of Business intelligence, performance management, quality of experience, trust, privacy, and usability security.
Master’s Degree in System Science, University Of Ottawa, Canada
Thesis title: A Comparative Study of Ensemble Active Learning.
Bachelor’s in computer & Information System, king faisal university, Saudi Arabia
Alabdulrahman, R., & Viktor, H. (2021). Catering for Unique Tastes: Targeting Grey-Sheep Users Recommender Systems through One-Class Machine Learning. Expert Systems with Applications 166: 114061
Alabdulrahman, R., & Viktor, H. Personalised Recommendation Systems and the Impact of COVID-19: Perspectives, Opportunities and Challenges. (2021). Paper presented at the Proceeding of the 12th International Joint Conference of Knowledge Discovery, Knowledge Engineering and Knowledge Management, KDIR2020.
Alabdulrahman, R., H. Viktor and E. Paquet (2019). Active Learning and Deep Learning for the Cold-Start Problem in Recommendation System: A Comparative Study. Knowledge Discovery, Knowledge Engineering and Knowledge Management, Cham, Springer International Publishing.
Alabdulrahman, R., Viktor, H., & Paquet, E. (2020). HCC-Learn Framework for Hybrid Learning in Recommender Systems. in Knowledge Discovery, Knowledge Engineering and Knowledge Management, CCIS. 2020, Springer Nature.
Alabdulrahman, R., Viktor, H., & Paquet, E. (2019). Active Learning and User Segmentation for the Cold-start Problem in Recommendation Systems. Paper presented at the Proceeding of the 11th International Joint Conference of Knowledge Discovery, Knowledge Engineering and Knowledge Management, Vienna: Austria, Volume 1, KDIR2019.
Alabdulrahman, R., Viktor, H., & Paquet, E. (2018). Beyond k-NN: Combining Cluster Analysis and Classification for Recommender Systems. Paper presented at the Proceeding of the 10th International Joint Conference of Knowledge Discovery, Knowledge Engineering and Knowledge Management, Seville: Spain, Volume 1, pp. 82-91.
Alabdulrahman, R., Viktor, H., & Paquet, E. (2016). An Active Learning Approach for Ensemble-based Data Stream Mining. Paper presented at the Proceeding of the 8th International Joint Conference of Knowledge Discovery, Knowledge Engineering and Knowledge Management, Porto: Portugal, Volume 1, pp. 275-282.
Fall 2023/2024
Undergraduate course:
MISY 2312: Introductory Programming for Information Systems
BUSI 3341: Business Analytics
Spring 2022/2023
Undergraduate course:
MISY 3332: Adv. Prog. Cnpts for info sys
BUSI 3341: Business Analytics
Graduate Courses:
MBA 6301: E-Commerce & Digital Marketing
Fall 2022/2023
Undergraduate course:
BUSI 3341: Business Analytics
MISY 2312: Introductory Programming for Information Systems
MISY 3312: Introduction to Telecommunications
Graduate Courses:
EMBA 4313: Project
MBA 6202: Independent Research
Spring 2021/2022
MISY 2312: Introductory Programming for Information Systems
MISY 2311: Introductory to Management Information Systems
Fall 2021/2022
MISY 2312: Introductory Programming for Information Systems
MISY 3311: Database Management for Information Systems
