Results 31 to 40 of about 649,217 (300)
Knowledge graph embeddings: open challenges and opportunities
, 2023 While Knowledge Graphs (KGs) have long been used as valuable sources of structured knowledge, in recent years, KG embeddings have become a popular way of deriving numeric vector representations from them, for instance, to support knowledge graph ...
Russa Biswas +9 more
core +1 more source
Ultrahyperbolic Knowledge Graph Embeddings
, 2022 Recent knowledge graph (KG) embeddings have been advanced by hyperbolic geometry due to its superior capability for representing hierarchies. The topological structures of real-world KGs, however, are rather heterogeneous, i.e., a KG is composed of ...
Staab, S +13 more
core +1 more source
Ars Mathematica Contemporanea, 2019 Summary: Let \(G\) be a ribbon graph and \(\mu (G)\) be the number of components of the virtual link formed from \(G\) as a cellularly embedded graph via the medial construction. In this paper we first prove that \(\mu (G) \leq f(G) + \gamma (G)\), where \(f(G)\) and \(\gamma (G)\) are the number of boundary components and Euler genus of \(G ...
Jin, Xian'an, Yan, Qi
openaire +3 more sources
Intrusion Detection Model Based on Graph Edge Feature Attention [PDF]
Jisuanji gongchengIntrusion detection is a cybersecurity technique designed to detect and prevent unauthorized access or attacks. Existing intrusion detection models demonstrate good detection performance for evenly distributed network data.
SHEN Xueli, LIU Shifeng
doaj +1 more source
Spectral embedding of graphs [PDF]
Pattern Recognition, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bin Luo 0001 +2 more
openaire +3 more sources
Distance measures for embedded graphs [PDF]
Computational Geometry, 2021 We introduce new distance measures for comparing straight-line embedded graphs based on the Fréchet distance and the weak Fréchet distance. These graph distances are defined using continuous mappings and thus take the combinatorial structure as well as the geometric embeddings of the graphs into account.
Hugo A. Akitaya +4 more
openaire +7 more sources
Universal Knowledge Graph Embeddings
, 2022 The dataset provides embeddings for entities and relations in DBpedia (English) and Wikidata. The two knowledge graphs are first merged using a novel approach that we developed by leveraging the sameAs links between them.
Ngomo, Axel-Cyrille Ngonga +6 more
core +1 more source
An Effective Knowledgeable Label-Aware Approach for Sentential Relation Extraction
Applied Sciences, 2023 In recent years, sentential relation extraction has made remarkable progress with text and knowledge graphs (KGs). However, existing architectures ignore the valuable information contained in relationship labels, which KGs provide and can complement the ...
Binling Nie, Yiming Shao
doaj +1 more source
Vertex sparsifiers : new results from old techniques [PDF]
, 2014 Given a capacitated graph $G = (V,E)$ and a set of terminals $K \subseteq V$, how should we produce a graph $H$ only on the terminals $K$ so that every (multicommodity) flow between the terminals in $G$ could be supported in $H$ with low congestion, and ...
Gupta, Anupam +10 more
core +1 more source
Interest-Aware Contrastive-Learning-Based GCN for Recommendation
IEEE Access, 2022 Graph convolutional networks (GCNs) have shown great potential in recommender systems. GCN models contain multiple layers of graph convolutions to exploit signals from higher-order neighbors.
Chuan Lin, Wei Zhou, Junhao Wen
doaj +1 more source