Results 21 to 30 of about 8,419,643 (305)
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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Network representation learning systematic review: Ancestors and current development state
Machine Learning with Applications, 2021 Real-world information networks are increasingly occurring across various disciplines including online social networks and citation networks. These network data are generally characterized by sparseness, nonlinearity and heterogeneity bringing different ...
Amina Amara +2 more
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Sustainability, 2023 In the digital economy context, enterprises’ competitive environment is changing rapidly. Historically, enterprises rely on a solitary fight to occupy the market.
Chen Ge, Wendong Lv, Junli Wang
semanticscholar +1 more source
CSNE: Conditional Signed Network Embedding [PDF]
, 2020 Signed networks are mathematical structures that encode positive and negative relations between entities such as friend/foe or trust/distrust. Recently, several papers studied the construction of useful low-dimensional representations (embeddings) of ...
Belkin Mikhail +10 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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Heterogeneous Information Network Embedding for Recommendation [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2017 Due to the flexibility in modelling data heterogeneity, heterogeneous information network (HIN) has been adopted to characterize complex and heterogeneous auxiliary data in recommender systems, called HIN based recommendation.
C. Shi +3 more
semanticscholar +1 more source
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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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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A Survey on Network Embedding [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2017 Network embedding assigns nodes in a network to low-dimensional representations and effectively preserves the network structure. Recently, a significant amount of progresses have been made toward this emerging network analysis paradigm.
Peng Cui, Xiao Wang, J. Pei, Wenwu Zhu
semanticscholar +1 more source
Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks [PDF]
The Web Conference, 2021 A bipartite network is a graph structure where nodes are from two distinct domains and only inter-domain interactions exist as edges. A large number of network embedding methods exist to learn vectorial node representations from general graphs with both ...
Hansheng Xue +5 more
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