Dr. Shaghayegh Sahebi

Shaghayegh Sahebi

Human-centered data mining including educational data mining, recommender and personalization systems, and user modeling

The World Within Reach

 

Introduction

Dr. Shaghayegh Sahebi is an Assistant Professor in the Department of Computer Science. She recently earned her PhD at the University of Pittsburgh. Her scholarly interests include application of Machine Learning in Recommender Systems, Educational Data Mining, and Social Networks.  Her research is focused on finding creative ways to use external information in these problems, adopting approaches such as Transfer Learning, Tensor Factorization, and Topic Models.  

Education

Ph.D. Intelligent Systems Program 2016
University of Pittsburgh, Pittsburgh, PA  

M.Sc. Intelligent Systems Program 2013
University of Pittsburgh, Pittsburgh, PA  

M.Sc. Computer Software Engineering 2009
University of Tehran, Tehran, Iran  

B.Sc. Computer Science/Engineering 2005
Sharif University of Technology, Tehran, Iran 

Research Interests

Dr. Sahebi is broadly interested in application of Machine Learning in Recommender Systems, Educational DataMining, and Social Networks. Her research is focused on finding creative ways to use external information in these problems, adopting approaches such as Transfer Learning, Tensor Factorization, and Topic Models. She particularly enjoys interdisciplinary and collaborative research. Here is a more detailed list of her research interests:

  • Recommender Systems, Cross-Domain Recommendation, External Information Usage in Collaborative Filtering, Community-Based Recommender Systems

  • Educational Data Mining, Predicting Student Performance, Concept Mining, Educational Sequencing

  • Social Network Analysis, Multi-Dimensional Community Detection in Social Networks, Scholar Networks 

Publications

Book Chapters 

D. Parra and S. Sahebi, “Recommender systems: Sources of knowledge and evaluation metrics,” in Advanced Techniques in Web Intelligence-2: Web User Browsing Behaviour and Preference Analysis, J. V. et al. (Eds.), Ed. Berlin Heidelberg: Springer-Verlag, 2013, ch. 7, pp. 149–175. 

Conference & Workshop Papers

S. Sahebi, Y. Lin, and P. Brusilovsky, “Tensor factorization for student modeling and performance prediction in unstructured domain,” in The 9th International Conference on Educational Data Mining. IEDMS, 2016. 

S. Sahebi and P. Brusilovsky, “It takes two to tango: An exploration of domain pairs for cross-domain collaborative filtering,” in Proceedings of the 9th ACM Conference on Recommender Systems. ACM, 2015, pp. 131–138. 

S. Sahebi, Y. Huang, and P. Brusilovsky, “Predicting student performance in solving parameterizedexercises,” in Intelligent Tutoring Systems. Springer, 2014, pp. 496–503. 

S. Sahebi and T. Walker, “Content-based cross-domain recommendations using segmented models,”in Workshop on New Trends in Content-based Recommender Systems (CBRecsys). ACM, 2014, pp. 57–63. 

J. Guerra,  S. Sahebi, P. Brusilovsky, and Y. Lin, “The problem solving genome: Analyzing sequentialpatterns of student work with parameterized exercises,” in 7th International Conference on Educational Data Mining, 2014, pp. 153–160. 

S. Sahebi, Y. Huang, and P. Brusilovsky, “Parameterized exercises in java programming: usingknowledge structure for performance prediction,” in The second Workshop on AI-supported Education for Computer Science (AIEDCS). University of Pittsburgh, 2014, pp. 61–70. S.

Sahebi and P. Brusilovsky, “Cross-domain collaborative recommendation in a cold-start context:The impact of user profile size on the quality of recommendation,” in User Modeling, Adaptation, and Personalization. Springer, 2013, pp. 289–295. 

C. Lopez, R. Farzan,  S. Sahebi, and P. Brusilovsky, “What influences the decision to participate inaudience-bounded online communities?” in iConference 2013 Proceedings, 2013, pp. 491–496. 

S.Sahebi and W. W. Cohen, “Community-based recommendations: a solution to the cold startproblem,” in Workshop on Recommender Systems and the Social Web, RSWEB. ACM, 2011. 

P. Brusilovsky, D. Parra,  S. Sahebi, and C. Wongchokprasitti, “Collaborative information finding in smaller communities: The case of research talks,” in Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2010 6th International Conference on. IEEE, 2010, pp. 1–10. 

S. Sahebi, C. Wongchokprasitti, and P. Brusilovsky, “Recommending research colloquia: a studyof several sources for user profiling,” in Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems. ACM, 2010, pp. 32–38. 

R. Khosravi, M. Sirjani, N. Asoudeh,  S. Sahebi, and H. Iravanchi, “Modeling and analysis of reo connectors using alloy,” in Coordination Models and Languages. Springer, 2008, pp. 169–183. 

S. Sahebi, F. Oroumchian, and R. Khosravi, “An enhanced similarity measure for utilizing sitestructure in web personalization systems,” in Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT’08. IEEE/WIC/ACM International Conference on, vol. 3. IEEE, 2008, pp. 82–85. 

S. Sahebi, F. Oroumchian, and R. Khosravi, “Applying and comparing hidden markov model and fuzzy clustering algorithms to web usage data for recommender systems,” in Data Mining and Knowledge Discovery, 2008, pp. 179–181. 

Posters

D. Parra, W. Jeng, P. Brusilovsky, C. López, and  S. Sahebi, “Conference navigator 3: An online social conference support system.” in UMAP Workshops, 2012.