Related papers: KCN: Knowledge Centric Networking

Content-Centric Networking (CCN) is an internetworking paradigm that offers an alternative to today's IP-based Internet Architecture. Instead of focusing on hosts and their locations, CCN emphasizes addressable named content. By decoupling…

A knowledge market can be described as a type of market where there is a consistent supply of data to satisfy the demand for information and is responsible for the mapping of potential problem solvers with the entities which need these…

A complex network is a condensed representation of the relational topological framework of a complex system. A main reason for the existence of such networks is the transmission of items through the entities of these complex systems. Here,…

The deep financial and economic crisis, which still characterizes these years, requires searching for tools in order to enhance knowledge sharing, creativity and innovation. The Internet is one of these tools that represents a practically…

The flux of social media and the convenience of mobile connectivity has created a mobile data phenomenon that is expected to overwhelm the mobile cellular networks in the foreseeable future. Despite the advent of 4G/LTE, the growth rate of…

Knowledge tracing---where a machine models the knowledge of a student as they interact with coursework---is a well established problem in computer supported education. Though effectively modeling student knowledge would have high…

Interactions are central to intelligent reasoning and learning abilities, with the interpretation of abstract knowledge guiding meaningful interaction with objects in the environment. While humans readily adapt to novel situations by…

Collaborative learning has emerged as a key paradigm in large-scale intelligent systems, enabling distributed agents to cooperatively train their models while addressing their privacy concerns. Central to this paradigm is knowledge…

Content-Centric Networking (CCN) naturally supports multi-path communication, as it allows the simultaneous use of multiple interfaces (e.g. LTE and WiFi). When multiple sources and multiple clients are considered, the optimal set of…

Online user innovation communities are becoming a promising source of user innovation knowledge and creative users. With the purpose of identifying valuable innovation knowledge and users, this study constructs an integrated super-network…

Software-defined networks (SDNs) are a huge evolution in simplifying implementation and network operation which have reduced costs and made the network programmable. Although SDNs are a suitable option for solving some of the previous…

Content-Centric Networking (CCN) is a communication paradigm that emphasizes content distribution. Named-Data Networking (NDN) is an instantiation of CCN, a candidate Future Internet Architecture. NDN supports human-readable content naming…

In this paper, we propose a method for knowledge graph construction in power distribution networks. This method leverages entity features, which involve their semantic, phonetic, and syntactic characteristics, in both the knowledge graph of…

We propose a novel technique to enhance Knowledge Graph Reasoning by combining Graph Convolution Neural Network (GCN) with the Attention Mechanism. This approach utilizes the Attention Mechanism to examine the relationships between entities…

We demonstrated, for the first time, a machine-learning method to assist the coexistence between quantum and classical communication channels. Software-defined networking was used to successfully enable the key generation and transmission…

Knowledge graphs are an efficient method for representing and connecting information across various concepts, useful in reasoning, question answering, and knowledge base completion tasks. They organize data by linking points, enabling…

Graph convolutional networks (GCNs) -- which are effective in modeling graph structures -- have been increasingly popular in knowledge graph completion (KGC). GCN-based KGC models first use GCNs to generate expressive entity representations…

The convergence of Information Technology (IT) and Operational Technology (OT) is a critical enabler for achieving autonomous and intelligent industrial systems. However, the increasing complexity, heterogeneity, and real-time demands of…

In this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicate to…

With the current host-based Internet architecture, networking faces limitations in dynamic scenarios, due mostly to host mobility. The ICN paradigm mitigates such problems by releasing the need to have an end-to-end transport session…