4 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…
Relations Prediction for Knowledge Graph Completion using Large Language Models
Sakher Khalil Alqaaidi, Krzysztof Kochut
Knowledge Graphs have been widely used to represent facts in a structured format. Due to their large scale applications, knowledge graphs suffer from being incomplete. The relation…
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…
Knowledge Graph Completion using Structural and Textual Embeddings
Sakher Khalil Alqaaidi, Krzysztof Kochut
Knowledge Graphs (KGs) are widely employed in artificial intelligence applications, such as question-answering and recommendation systems. However, KGs are frequently found to be i…