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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
RDF Data Visualization in Web Browsers
 Škrobánek, Kristián ; Polčák, Libor (referee) ; Burget, Radek (advisor)
This diploma thesis focuses on graph database data visualization, where data is stored in RDF format. Standard visualisation of RDF data in tables does not offer sufficiently usable user view. One of the goals of this work is to show RDF data in interactive graph, which is ideal form of viewing data considering lucidity and information value. The graph gives good view of not only the data itself but also relationships between the data. Another goal is to test ability of browsers to visualize large amounts of data.
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RDF Data Visualization in Web Browsers
 Škrobánek, Kristián ; Polčák, Libor (referee) ; Burget, Radek (advisor)
This diploma thesis focuses on graph database data visualization, where data is stored in RDF format. Standard visualisation of RDF data in tables does not offer sufficiently usable user view. One of the goals of this work is to show RDF data in interactive graph, which is ideal form of viewing data considering lucidity and information value. The graph gives good view of not only the data itself but also relationships between the data. Another goal is to test ability of browsers to visualize large amounts of data.
Detailed record
Graph data analysis using deep learning methods
 Vancák, Vladislav ; Svoboda, Martin (advisor) ; Majerech, Vladan (referee)
The goal of this thesis is to investigate the existing graph embedding methods. We aim to represent the nodes of undirected weighted graphs as low-dimensional vectors, also called embeddings, in order to create a rep- resentation suitable for various analytical tasks such as link prediction and clustering. We first introduce several contemporary approaches allowing to create such network embeddings. We then propose a set of modifications and improvements and assess the performance of the enhanced models. Finally, we present a set of evaluation metrics and use them to experimentally evalu- ate and compare the presented techniques on a series of tasks such as graph visualisation and graph reconstruction. 1
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