Zefeng Gu, Hua Chen^*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2497-2514, 2023, DOI:10.32604/cmes.2023.024332 - 23 November 2022

Abstract Link prediction, also known as Knowledge Graph Completion (KGC), is the common task in Knowledge Graphs (KGs) to predict missing connections between entities. Most existing methods focus on designing shallow, scalable models, which have less expressive than deep, multi-layer models. Furthermore, most operations like addition, matrix multiplications or factorization are handcrafted based on a few known relation patterns in several well-known datasets, such as FB15k, WN18, etc. However, due to the diversity and complex nature of real-world data distribution, it is inherently difficult to preset all latent patterns. To address this issue, we propose KGE-ANS, More >

S. Kalavathi^1,*, R. Nedunchelian²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 39-56, 2023, DOI:10.32604/iasc.2023.031522 - 29 September 2022

Abstract Network analysis is a promising field in the area of network applications as different types of traffic grow enormously and exponentially. Reliable route prediction is a challenging task in the Large Scale Networks (LSN). Various non-self-learning and self-learning approaches have been adopted to predict reliable routing. Routing protocols decide how to send all the packets from source to the destination addresses across the network through their IP. In the current era, dynamic protocols are preferred as they network self-learning internally using an algorithm and may not entail being updated physically more than the static protocols.… More >

Minghu Tang^1,2,3,*, Wei Yu⁴, Xiaoming Li⁴, Xue Chen⁵, Wenjun Wang³, Zhen Liu⁶

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1069-1084, 2022, DOI:10.32604/csse.2022.028841 - 09 May 2022

Abstract Link prediction has attracted wide attention among interdisciplinary researchers as an important issue in complex network. It aims to predict the missing links in current networks and new links that will appear in future networks. Despite the presence of missing links in the target network of link prediction studies, the network it processes remains macroscopically as a large connected graph. However, the complexity of the real world makes the complex networks abstracted from real systems often contain many isolated nodes. This phenomenon leads to existing link prediction methods not to efficiently implement the prediction of… More >

Puneet Garg^*, Ashutosh Dixit, Preeti Sethi

Computer Systems Science and Engineering, Vol.40, No.2, pp. 703-717, 2022, DOI:10.32604/csse.2022.019557 - 09 September 2021

Abstract Opportunistic Networks (OppNets) is gaining popularity day-by-day due to their various applications in the real-life world. The two major reasons for its popularity are its suitability to be established without any requirement of additional infrastructure and the ability to tolerate long delays during data communication. Opportunistic Network is also considered as a descendant of Mobile Ad hoc Networks (Manets) and Wireless Sensor Networks (WSNs), therefore, it inherits most of the traits from both mentioned networking techniques. Apart from its popularity, Opportunistic Networks are also starting to face challenges nowadays to comply with the emerging issues of… More >