Results 31 to 40 of about 4,728,201 (299)
Research on Service Recommendation Method of Multi-network Hybrid Embed-ding Learning [PDF]
Jisuanji kexue yu tansuo, 2022 The network embedding method can map the network nodes to a low-dimensional vector space and ext-ract the feature information of each node effectively. In the field of service recommendation, some studies show that the introduction of network embedding ...
WANG Xuechun, LYU Shengkai, WU Hao, HE Peng, ZENG Cheng
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A Network Embedding Algorithm Preserving Community Structure Information [PDF]
Jisuanji gongcheng, 2021 Most existing network embedding algorithms only retain the micro-structure information of the network, but ignore the community structure information which is important in networks.In order to incorporate the community structure information into the ...
Lü Shaoqing, ZHAO Xueli, ZHANG Pan, REN Xincheng
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Heterogeneous Information Network Representation Learning Incorporating Community Structure
IEEE Access, 2022 Network embedding usually learns the node representations using their local context information. However, as an important mesoscopic description of network structures, community structures hidden in the networks have been largely ignored.
Wei Yu +5 more
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Fusion of text and graph information for machine learning problems on networks [PDF]
PeerJ Computer Science, 2021 Today, increased attention is drawn towards network representation learning, a technique that maps nodes of a network into vectors of a low-dimensional embedding space.
Ilya Makarov +2 more
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Network Embedding For Brain Connectivity [PDF]
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021 In Neurosciences, networks are currently used for representing the brain connections system with the purpose of determining the specific characteristics of the brain itself. However, discriminating between a healthy human brain network and a pathological one using common network descriptors could be misleading.
Carboni, Lucrezia +2 more
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A Link Stress-related Virtual Network Embedding Algorithm [PDF]
Jisuanji gongcheng, 2016 Aiming at the problem of high link stress in substrate network caused by traditional Virtual Network Embedding(VNE) algorithm,a new VNE algorithm is proposed.In the stage of node embedding,the importance degree of node in network is gotten by its ...
ZHANG Jingjing,ZHAO Chenggui,YUAN Jianming
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SINE: Second-Order Information Network Embedding
IEEE Access, 2020 As an important data type, the demand of network analysis and learning is increasingly prominent. A key problem of network analysis is to study how to reasonably represent the feature information in the network, that is network embedding. However, in the
Ziqi Wang +3 more
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IEEE Transactions on Image Processing, 2020 Superpixel segmentation is a fundamental computer vision technique that finds application in a multitude of high level computer vision tasks. Most state-of-the-art superpixel segmentation methods are unsupervised in nature and thus cannot fully utilize frequently occurring texture patterns or incorporate multiscale context.
Utkarsh Gaur, B. S. Manjunath
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Computing the nearest euclidean distance matrix with low embedding dimensions [PDF]
, 2013 Euclidean distance embedding appears in many high-profile applications including wireless sensor network localization, where not all pairwise distances among sensors are known or accurate.
Qi, Hou-Duo, Yuan, Xiaoming, Qi, Hou Duo
core +1 more source
Service Embedding in IoT Networks [PDF]
IEEE Access, 2020 The Internet of Things is anticipated to participate in the execution of a variety of complex tasks in the near future. IoT objects capable of handling multiple sensing and actuating functions are the cornerstone of smart applications such as smart buildings, smart factories, home automation, and healthcare automation.
Haider Qays Al-Shammari +3 more
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