A5002336714- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Distributed and Parallel Computing Systems
- Cloud Computing and Resource Management
- Advanced Clustering Algorithms Research
- Advanced Graph Neural Networks
- Parallel Computing and Optimization Techniques
- Peer-to-Peer Network Technologies
- Metaheuristic Optimization Algorithms Research
- Scientific Computing and Data Management
- Distributed systems and fault tolerance
- Caching and Content Delivery
- IoT and Edge/Fog Computing
- Rough Sets and Fuzzy Logic
- Face and Expression Recognition
- Text and Document Classification Technologies
- Recommender Systems and Techniques
- Spam and Phishing Detection
- Mental Health Research Topics
- Anomaly Detection Techniques and Applications
- Advanced Computing and Algorithms
- Digital Marketing and Social Media
- Data Mining Algorithms and Applications
- IoT-based Smart Home Systems
- Advanced Algorithms and Applications
Istinye University
2023-2024
Azarbaijan Shahid Madani University
2015-2024
Islamic Azad University, Tehran
2009-2013
University of Technology Malaysia
2008-2011
Islamic Azad University of Tabriz
2009
As the community detection is able to facilitate discovery of hidden information in complex networks, it has been drawn a lot attention recently. However, due growth computational power and data storage, scale these networks grown dramatically. In order detect communities by utilizing global approaches, required have all whole network; something which impossible, because rapid size networks. this paper, local approach proposed based on expansion core nodes. First, community's central node...
Community detection in large-scale networks is one of the main challenges social analysis. Proposing a fast and accurate algorithm with low time complexity vital for networks. In this paper, community based on local balanced label diffusion (LBLD) proposed. The LBLD starts assigning node importance score to each using new similarity measure. After that, top 5% important nodes are selected as initial rough cores expand communities. first step, two neighbor highest than others receive same...
Community detection is an essential approach for analyzing the structural and functional properties of complex networks. Although many community algorithms have been recently presented, most them are weak limited in different ways. Label Propagation Algorithm (LPA) a well-known efficient technique which characterized by merits nearly-linear running time easy implementation. However, LPA has some significant problems such as instability, randomness, monster detection. In this paper,...
The optimum use of energy in wireless sensor networks (WSNs) is very important. recent researches show that organising the network nodes some clusters leads to higher efficiency and finally it increases lifetime network. So, controlling number location head (CHs) also size about node a balance CHs increasing Clustering-based routing protocols are energy-efficient improve objective clustering minimise total transmission power by aggregating into single path for prolonging lifetime. In this...
cloud computing is a dynamically scalable system that provides internet-based services, often virtually. With emergence of electronic systems and removal paper, virtual technologies electronics are becoming important. This paper discusses the importance online training emphasizes on its qualitative quantitative development for some organizations or technical science engineering students. mainly concentrates utilizing education based environments. We discuss necessity cloud-based educational...
The main goal in the influence maximization problem (IMP) is to find k minimum nodes with highest spread on social networks. Since IMP NP-hard and not possible obtain optimum results, it considered by heuristic algorithms. Many strategies focus power of core influential nodes. Most detection-based methods concentrate often give same for all best core. However, some other fairly have potential select as seed less important cores, because these can play an role diffusion information among...
Community detection in complex networks often suffers from insufficient data and limited utilization of prior knowledge. In this paper we propose "Semi-supervised Generative Adversarial Network" (GANSE), a novel algorithm that integrates Networks (GANs) semi-supervised learning to address these challenges. This method addresses the issues above through multi-step process. Initially, network is rewired using vertex similarity metrics, thereby enhancing its structural integrity. Subsequently,...