14 documents found, page 1 of 2
DualRep: Knowledge Graph Completion by Utilizing Dual Representation of Relatio...
Gul, Haji; Al-Obeidat, Feras; Amin, Adnan; Wasim, Muhammad; Moreira, FernandoKnowledge graphs (KGs) possess a vital role in enhancing the semantic comprehension of extensive datasets across many fields. It facilitate activities like recommendation systems, semantic searching, and intelligent data mining. However, lacking information can sometimes limit the usefulness of knowledge graphs (KGs), as the lack of relationships between entities could severely limit their practical application...
Effectiveness of internal evaluation metrics for community detection based on c...
Wasim, Muhammad; Ullah, Ubaid; Al-Obeidat, Feras; Amin, Adnan; Moreira, FernandoThe exploration of complex networks and the arrangement of communities is a widely researched topic across various fields, reflecting research interest in a multitude of domains. Clustering algorithms have emerged as a prominent tool for community detection, gaining considerable attention in recent decades. To assess the effectiveness of clustering algorithms, various evaluation metrics are employed, including ...
Advancing fake news detection with Graph Neural Network and Deep Learning
Gul, Haji; Al-Obeidat, Feras; Wasim, Muhammad; Amin, Adnan; Moreira, FernandoIn the modern era of digital technology, the rapid distribution of news via social media platforms substantially contributes to the propagation of false information, presenting challenges in upholding the accuracy and reliability of information. This study presents an updated approach that utilizes Graph Neural Networks (GNNs) alongside with advanced deep learning techniques to improve the identification of fal...
Target-vs-One and Target-vs-All Classification of Epilepsy using deep learning ...
Amin, Adnan; Al-Obeidat, Feras; Algeelani, Nasir Ahmed; Shudaiber, Ahmed; Moreira, FernandoWith the pervasive generation of medical data, there is a need for the worldwide medical and health care sector to find appropriate computational intelligence techniques for various medical conditions such as epilepsy seizures (ES). ES is a brain disorder that affects people of all ages, is a chronic, non-communicable disease, and can occur for no apparent reason owing to a genetic defect at any time. The unpre...
DDoS Attack Detection in Edge-IIoT Network using Ensemble Learning
Laiq, Fariba; Al-Obeidat, Feras; Amin, Adnan; Moreira, FernandoAs the number of IoT devices increases daily due to the rapid growth in technology, every device and network is vulnerable to attacks because it is exposed to the internet. Denial of Service (DoS) is a prevalent type of intrusion on the Internet of Things (IoT) network in which the server becomes down due to flooding requests. Distributed Denial of Service (DDoS) is a special type of DoS attack where the networ...
Analyzing complex networks: Extracting key characteristics and measuring struct...
Gul, Haji; Al-Obeidat, Feras; Amin, Adnan; Moreira, FernandoThis paper discusses the importance of feature extraction and structure similarity measurement in the analysis of complex networks. Social networks, biological systems, and transportation networks are just a few examples of the many phenomena that have been modeled using complex networks. However, analyzing these networks can be challenging due to their large size and complexity. Feature extraction techniques c...
Enhancing link prediction efficiency with shortest path and structural attributes
Wasim, Muhammad; Al-Obeidat, Feras; Amin, Adnan; Gul, Haji; Moreira, FernandoLink prediction is one of the most essential and crucial tasks in complex network research since it seeks to forecast missing links in a network based on current ones. This problem has applications in a variety of scientific disciplines, including social network research, recommendation systems, and biological networks. In previous work, link prediction has been solved through different methods such as path, so...
Forecasting Networks Links with Laplace Characteristic and Geographical Informa...
Wasim, Muhammad; Al-Obeidat, Feras; Gul, Haji; Amin, Adnan; Moreira, FernandoForecasting links in a network is a crucial task in various applications such as social networks, internet traffic management, and data mining. Many studies on forecasting links in social networks and on other networks have been conducted over the last decade. In this paper, we propose a novel method based on graph Laplacian eigenmaps for predicting the geographic location of nodes in complex networks. Our meth...
Comparative analysis of machine learning algorithms for author age and gender i...
Zainab, Zarah; Al-Obeidat, Feras; Gul, Haji; Amin, Adnan; Moreira, FernandoAuthor profiling is part of information retrieval in which different perspectives of the author are observed by considering various characteristics like native language, gender, and age. Different techniques are used to extract the required information using text analysis, like author identification on social media and for Short Text Message Service. Author profiling helps in security and blogs for identificati...
Hill Climbing-Based Efficient Model for Link Prediction in Undirected Graphs
Gul, Haji; Al-Obeidat, Feras; Amin, Adnan; Huang, Kaizhu; Moreira, FernandoLink prediction is a key problem in the field of undirected graph, and it can be used in a variety of contexts, including information retrieval and market analysis. By “undirected graphs”, we mean undirected complex networks in this study. The ability to predict new links in complex networks has a significant impact on society. Many complex systems can be modelled using networks. For example, links represent re...