686 citations · 1.5k across the 39 of their papers we have counts for
46 papers
A Survey on Recent Random Walk-based Methods for Embedding Knowledge Graphs
Elika Bozorgi, Sakher Khalil Alqaiidi, Afsaneh Shams +2
Machine learning, deep learning, and NLP methods on knowledge graphs are present in different fields and have important roles in various domains from self-driving cars to friend re…
Subgraph2vec: A random walk-based algorithm for embedding knowledge graphs
Elika Bozorgi, Saber Soleimani, Sakher Khalil Alqaiidi +2
Graph is an important data representation which occurs naturally in the real world applications \cite{goyal2018graph}. Therefore, analyzing graphs provides users with better insigh…
Students Success Modeling: Most Important Factors
Sahar Voghoei, James M. Byars, Scott Jackson King +4
The importance of retention rate for higher education institutions has encouraged data analysts to present various methods to predict at-risk students. The present study, motivated…
Deep Learning in Healthcare: An In-Depth Analysis
Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, Khaled M. Rasheed +1
Deep learning (DL) along with never-ending advancements in computational processing and cloud technologies have bestowed us powerful analyzing tools and techniques in the past deca…
Word Embedding Neural Networks to Advance Knee Osteoarthritis Research
Soheyla Amirian, Husam Ghazaleh, Mehdi Assefi +4
Osteoarthritis (OA) is the most prevalent chronic joint disease worldwide, where knee OA takes more than 80% of commonly affected joints. Knee OA is not a curable disease yet, and…
3D-model ShapeNet Core Classification using Meta-Semantic Learning
Farid Ghareh Mohammadi, Cheng Chen, Farzan Shenavarmasouleh +3
Understanding 3D point cloud models for learning purposes has become an imperative challenge for real-world identification such as autonomous driving systems. A wide variety of sol…