6 citations · 13 across the 4 of their papers we have counts for
4 papers
Knowledge Graph-based Session Recommendation with Adaptive Propagation
Yu Wang, Amin Javari, Janani Balaji +3
Session-based recommender systems (SBRSs) predict users' next interacted items based on their historical activities. While most SBRSs capture purchasing intentions locally within e…
Hierarchical Multi-Task Learning Framework for Session-based Recommendations
Sejoon Oh, Walid Shalaby, Amir Afsharinejad +1
While session-based recommender systems (SBRSs) have shown superior recommendation performance, multi-task learning (MTL) has been adopted by SBRSs to enhance their prediction accu…
Solving Cold-Start Problem in Large-scale Recommendation Engines: A Deep Learning Approach
Jianbo Yuan, Walid Shalaby, Mohammed Korayem +3
Collaborative Filtering (CF) is widely used in large-scale recommendation engines because of its efficiency, accuracy and scalability. However, in practice, the fact that recommend…
Watsonsim: Overview of a Question Answering Engine
Sean Gallagher, Wlodek Zadrozny, Walid Shalaby +1
The objective of the project is to design and run a system similar to Watson, designed to answer Jeopardy questions. In the course of a semester, we developed an open source questi…