Evaluating a Graph Query Language for Human-Robot Interaction Data in Smart Environments

Author(s):  
Norman Köster ◽  
Sebastian Wrede ◽  
Philipp Cimiano
2015 ◽  
Vol 27 (7) ◽  
pp. 1824-1837 ◽  
Author(s):  
Jiwon Seo ◽  
Stephen Guo ◽  
Monica S. Lam

2017 ◽  
Author(s):  
Jonathan Blaney

Introduces core concepts of Linked Open Data, including URIs, ontologies, RDF formats, and a gentle intro to the graph query language SPARQL.


Author(s):  
Gábor Bergmann ◽  
Zoltán Ujhelyi ◽  
István Ráth ◽  
Dániel Varró

Author(s):  
Sherif Sakr ◽  
Ghazi Al-Naymat

Recently, there has been a lot of interest in the application of graphs in different domains. Graphs have been widely used for data modeling in different application domains such as: chemical compounds, protein networks, social networks and Semantic Web. Given a query graph, the task of retrieving related graphs as a result of the query from a large graph database is a key issue in any graph-based application. This has raised a crucial need for efficient graph indexing and querying techniques. In this chapter, we provide an overview of different techniques for indexing and querying graph databases. An overview of several proposals of graph query language is also given. Finally, we provide a set of guidelines for future research directions.


2013 ◽  
pp. 222-239
Author(s):  
Sherif Sakr ◽  
Ghazi Al-Naymat

Recently, there has been a lot of interest in the application of graphs in different domains. Graphs have been widely used for data modeling in different application domains such as: chemical compounds, protein networks, social networks and Semantic Web. Given a query graph, the task of retrieving related graphs as a result of the query from a large graph database is a key issue in any graph-based application. This has raised a crucial need for efficient graph indexing and querying techniques. In this chapter, we provide an overview of different techniques for indexing and querying graph databases. An overview of several proposals of graph query language is also given. Finally, we provide a set of guidelines for future research directions.


Author(s):  
Sherif Sakr ◽  
Ghazi Al-Naymat

Recently, there has been a lot of interest in the application of graphs in different domains. Graphs have been widely used for data modeling in different application domains such as: chemical compounds, protein networks, social networks, and Semantic Web. Given a query graph, the task of retrieving related graphs as a result of the query from a large graph database is a key issue in any graph-based application. This has raised a crucial need for efficient graph indexing and querying techniques. This chapter provides an overview of different techniques for indexing and querying graph databases. An overview of several proposals of graph query language is also given. Finally, the chapter provides a set of guidelines for future research directions.


2014 ◽  
Vol 6 (4) ◽  
pp. 940-953 ◽  
Author(s):  
Juha Röning ◽  
Jukka Holappa ◽  
Vili Kellokumpu ◽  
Antti Tikanmäki ◽  
Matti Pietikäinen

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