Results 51 to 60 of about 138,699 (301)
Applied Sciences, 2022 Aiming at the current situation of network embedding research focusing on dynamic homogeneous network embedding and static heterogeneous information network embedding but lack of dynamic information utilization, this paper proposes a dynamic ...
Hualong Bu +3 more
doaj +1 more source
From wide to deep: dimension lifting network for parameter-efficient knowledge graph embedding [PDF]
Knowledge graph embedding (KGE) that maps entities and relations into vector representations is essential for downstream applications. Conventional KGE methods require high-dimensional representations to learn the complex structure of knowledge graph ...
Zhang, He +6 more
core +1 more source
Exploring Network Embedding for Efficient Message Routing in Opportunistic Mobile Social Networks
, 2019 With the advancement in communication technologies and the widespread availability of mobile devices, the opportunistic mobile social networks (OMSNs) are gaining momentum in supporting spontaneous communication and interaction among end-users who ...
Yuan, Bo +7 more
core +1 more source
Multiple Network Embeddings into Hypercubes
Journal of Parallel and Distributed Computing, 1993 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ajay K. Gupta 0001, Susanne E. Hambrusch
openaire +3 more sources
Structural insights into an engineered feruloyl esterase with improved MHET degrading properties
FEBS Letters, EarlyView.A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa +5 more
wiley +1 more source
FEBS Letters, EarlyView.Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source
Semisupervised Community Preserving Network Embedding with Pairwise Constraints
Complexity, 2020 Network embedding aims to learn the low-dimensional representations of nodes in networks. It preserves the structure and internal attributes of the networks while representing nodes as low-dimensional dense real-valued vectors.
Dong Liu +4 more
doaj +1 more source
Susceptible-infected-spreading-based network embedding in static and temporal networks
EPJ Data Science, 2020 Link prediction can be used to extract missing information, identify spurious interactions as well as forecast network evolution. Network embedding is a methodology to assign coordinates to nodes in a low-dimensional vector space. By embedding nodes into
Xiu-Xiu Zhan +4 more
doaj +1 more source
Temporal self-attention network for medical concept embedding [PDF]
, 2019 © 2019 IEEE. In longitudinal electronic health records (EHRs), the event records of a patient are distributed over a long period of time and the temporal relations between the events reflect sufficient domain knowledge to benefit prediction tasks such as
Shen, Tao +17 more
core +1 more source
Influence of clustering coefficient on network embedding in link prediction
, 2022 Multiple network embedding algorithms have been proposed to perform the prediction of missing or future links in complex networks. However, we lack the understanding of how network topology affects their performance, or which algorithms are more likely ...
Fernández Robledo, O. (author) +7 more
core +1 more source