Search Results

Recent advances in network representation learning have sparked renewed interest in developing strategies for learning on spatio-temporal signals, crucial for applications like traffic forecasting, recommendation systems, and social network analysis. ...

Semi-supervised graph domain adaptation, as a subfield of graph transfer learning, seeks to precisely annotate unlabeled target graph nodes by leveraging transferable features acquired from the limited labeled source nodes. However, most existing studies ...

Attributed graphs are used to model a wide variety of real-world networks. Recent graph convolutional network-based representation learning methods have set state-of-the-art results on the clustering of attributed graphs. However, these approaches deal ...

In order to overcome the problems of low efficiency and poor accuracy of traditional abnormal data capture, this paper proposes an industrial IoT communication abnormal data capture method based on node clustering. First, analyse the structure of ...

Graph convolutional neural networks (GCN) have been the model of choice for graph representation learning, which is mainly due to the effective design of graph convolution that computes the representation of a node by aggregating those of its neighbors. ...

In this paper, we present a novel approach of automated evaluation of programming assignments (AEPA) the highlight of which is that it automatically identifies multiple solution approaches to the programming question from the set of submitted solutions. ...

Clustering is an efficient technique for saving energy of wireless sensor networks (WSNs). In this paper a two-level clustering approach is presented, combining a traditional gradient-based clustering technique with an evolutionary optimization ...

Multicast benefits data center group communication in both saving network traffic and improving application throughput. The SLA (Service Level Agreement) of cloud service requires the computation correctness of distributed applications, translating to ...

AbstractIn web search engines, such as Google, the ranking of a particular keyword is determined by mathematical tools, e.g., Pagerank or Hits. However, as the size of the network increases, it becomes increasingly difficult to use keyword ranking to ...

This paper presents a clustering protocol combined with a mobile sink (MS) solution for efficient data gathering in wireless sensor networks (WSNs). The main insight for the cluster creation method is drawn from image processing field and namely from ...

The pattern of interactions between individuals in a population contains implicitly within them a remarkable amount of information. This information, if extracted, could be of significant importance in several realms such as containing the spread of ...

A key decision when developing in-memory computing applications is choice of a mechanism to store and retrieve strings. The most efficient current data structures for this task are the hash table with move-to-front chains and the burst trie, both of ...

Detecting communities in real world networks is an important problem for data analysis in science and engineering. By clustering nodes intelligently, a recursive algorithm is designed to detect community. Since the relabeling of nodes does not alter the ...

A P2P network is an important computing model because of its scalability, adaptability, self-organization, etc. How to organize the nodes in P2P networks effectively is an important research issue. The node clustering aims to provide an effective method ...

Node clustering and subcarrier allocation are imperative to ameliorate system throughput and facilitate quality-of-service (QoS) provisioning by means of effective interference control and maximum frequency reuse. In this paper, we propose a novel node ...

Peer-to-peer (P2P) has become an important computing model because of its adaptation, self-organization and autonomy etc. But efficient organization of the nodes in P2P networks is still a challenge needs to be addressed. Node clustering is a mechanism ...