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

2018 ◽  
pp. 263-279 ◽  
Author(s):  
Norman Köster ◽  
Sebastian Wrede ◽  
Philipp Cimiano
Keyword(s):  
Query Language ◽  
Human Robot Interaction ◽  
Smart Environments ◽  
Interaction Data ◽  
Robot Interaction ◽  
Graph Query ◽  
Graph Query Language

SociaLite: An Efficient Graph Query Language Based on Datalog

2015 ◽  
Vol 27 (7) ◽  
pp. 1824-1837 ◽  
Author(s):  
Jiwon Seo ◽  
Stephen Guo ◽  
Monica S. Lam
Keyword(s):  
Query Language ◽  
Graph Query ◽  
Graph Query Language

scholarly journals Introduction to the Principles of Linked Open Data

2017 ◽  
Author(s):  
Jonathan Blaney
Keyword(s):  
Query Language ◽  
Open Data ◽  
Linked Open Data ◽  
Graph Query ◽  
Graph Query Language ◽  
Core Concepts

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

A Graph Query Language for EMF Models

2011 ◽  
pp. 167-182 ◽  
Author(s):  
Gábor Bergmann ◽  
Zoltán Ujhelyi ◽  
István Ráth ◽  
Dániel Varró
Keyword(s):  
Query Language ◽  
Graph Query ◽  
Graph Query Language

An Overview of Graph Indexing and Querying Techniques

2011 ◽  
pp. 71-88 ◽  
Author(s):  
Sherif Sakr ◽  
Ghazi Al-Naymat
Keyword(s):  
Social Networks ◽  
Query Language ◽  
Future Research ◽  
Protein Networks ◽  
Research Directions ◽  
Query Graph ◽  
Graph Indexing ◽  
Graph Query ◽  
Graph Query Language ◽  
Future Research Directions

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.

An Overview of Graph Indexing and Querying Techniques

2013 ◽  
pp. 222-239
Author(s):  
Sherif Sakr ◽  
Ghazi Al-Naymat
Keyword(s):  
Social Networks ◽  
Query Language ◽  
Future Research ◽  
Protein Networks ◽  
Research Directions ◽  
Query Graph ◽  
Graph Indexing ◽  
Graph Query ◽  
Graph Query Language ◽  
Future Research Directions

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.

Querying Graph Databases

2011 ◽  
pp. 304-322
Author(s):  
Sherif Sakr ◽  
Ghazi Al-Naymat
Keyword(s):  
Social Networks ◽  
Query Language ◽  
Future Research ◽  
Graph Databases ◽  
Research Directions ◽  
Query Graph ◽  
Graph Indexing ◽  
Graph Query ◽  
Graph Query Language ◽  
Future Research Directions

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.

Minotaurus: A System for Affective Human–Robot Interaction in Smart Environments

2014 ◽  
Vol 6 (4) ◽  
pp. 940-953 ◽  
Author(s):  
Juha Röning ◽  
Jukka Holappa ◽  
Vili Kellokumpu ◽  
Antti Tikanmäki ◽  
Matti Pietikäinen
Keyword(s):  
Human Robot Interaction ◽  
Smart Environments ◽  
Robot Interaction
Sign in / Sign up

Export Citation Format

Share Document