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metaphactory: A platform for knowledge graph management
In this system paper we describe metaphactory, a platform for building knowledge graph
applications. The metaphactory platform aims at supporting different categories of …
applications. The metaphactory platform aims at supporting different categories of …
Novel translation knowledge graph completion model based on 2D convolution
The knowledge graph completion task involves predicting missing entities and relations in a
knowledge graph. Many models have achieved good results, but they have become …
knowledge graph. Many models have achieved good results, but they have become …
Convolutional neural network knowledge graph link prediction model based on relational memory
M Shi, J Zhao, D Wu - Computational Intelligence and …, 2023 - Wiley Online Library
A knowledge graph is a collection of fact triples, a semantic network composed of nodes and
edges. Link prediction from knowledge graphs is used to reason about missing parts of …
edges. Link prediction from knowledge graphs is used to reason about missing parts of …
Complex Knowledge Graph Embeddings Based on Convolution and Translation
Link prediction involves the use of entities and relations that already exist in a knowledge
graph to reason about missing entities or relations. Different approaches have been …
graph to reason about missing entities or relations. Different approaches have been …
Knowledge graph embedding using a multi-channel interactive convolutional neural network with triple attention
Knowledge graph embedding (KGE) has been identified as an effective method for link
prediction, which involves predicting missing relations or entities based on existing entities …
prediction, which involves predicting missing relations or entities based on existing entities …
Complex knowledge graph embeddings based on convolution and translation
Link prediction involves the use of entities and relations that already exist in a knowledge
graph to reason about missing entities or relations. Different approaches have been …
graph to reason about missing entities or relations. Different approaches have been …
Semantic zooming approach to semantic link network visualization
D Litovkin, A Anikin, M Kultsova - … 16–19, 2019, Proceedings, Part II 3, 2019 - Springer
In the paper, we described a semantic zooming approach to the visualization of special kind
structures-semantic link networks (SLN), represented as a visual graph. The proposed …
structures-semantic link networks (SLN), represented as a visual graph. The proposed …
A comparative evaluation of visual and natural language question answering over linked data
With the growing number and size of Linked Data datasets, it is crucial to make the data
accessible and useful for users without knowledge of formal query languages. Two …
accessible and useful for users without knowledge of formal query languages. Two …