Paper Info
Title
Ontology modeling and storage system for robot context understanding
Abstract
A mobile robot that interacts with its environment needs a machine-understandable representation of objects and their usages. We present an ontology of objects, with generic shape representations obtained through form-function reasoning. Sets of objects are associated with typical human activities, which supports context understanding. We describe an efficient ontology document storage system, which is based on stable and well-known relational databases. We first design a relational data schema appropriate for Web Ontology Language (OWL) documents, and then develop a transformation mechanism from OWL documents to the relational schema.
Year
DOI
Venue
2005
10.1007/11553939_130
KES (3)
Keywords
Field
DocType
relational schema,relational data,form-function reasoning,web ontology language,machine-understandable representation,well-known relational databases,storage system,ontology modeling,context understanding,owl document,generic shape representation,efficient ontology document storage,robot context understanding,mobile robot,relational database
Ontology (information science),Ontology-based data integration,World Wide Web,Information retrieval,Process ontology,Relational database,Computer science,OWL-S,Suggested Upper Merged Ontology,Upper ontology,Distributed computing,Web Ontology Language
Conference
Volume
ISSN
ISBN
3683
0302-9743
3-540-28896-1
Citations 
PageRank 
References 
2
0.56
2
Authors
6
Name
Order
Citations
PageRank
Eric Wang1304.26
Yong Se Kim219120.22
Hak Soo Kim3101.91
Jin Hyun Son421718.21
Sanghoon Lee574097.47
Il Hong Suh6780110.60