Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
Principles of Database Systems
Principles of Database Systems
Active Database Systems: Triggers and Rules for Advanced Database Processing
Active Database Systems: Triggers and Rules for Advanced Database Processing
E-DEVICE: An Extensible Active Knowledge Base System with Multiple Rule Type Support
IEEE Transactions on Knowledge and Data Engineering
Semantic Matching of Web Services Capabilities
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Towards a Distributed Service-Oriented Business Rules System
ECOWS '05 Proceedings of the Third European Conference on Web Services
Event-triggered data and knowledge sharing among collaborating government organizations
dg.o '07 Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains
DL-Lite: tractable description logics for ontologies
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Scalable semantic retrieval through summarization and refinement
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
SILK: Higher Level Rules with Defaults and Semantic Scalability
RR '09 Proceedings of the 3rd International Conference on Web Reasoning and Rule Systems
LUBM: A benchmark for OWL knowledge base systems
Web Semantics: Science, Services and Agents on the World Wide Web
Realizing business processes with ECA rules: benefits, challenges, limits
PPSWR'06 Proceedings of the 4th international conference on Principles and Practice of Semantic Web Reasoning
Hi-index | 0.00 |
This paper presents an ontology management system and ontology processing techniques used to support a distributed event-triggered knowledge network (ETKnet), which has been developed for deployment in a national network for rapid detection and reporting of crop disease and pest outbreaks. The ontology management system, called Lyra, is improved to address issues of terminology mapping, rule discovery, and large ABox inference. A domain ontology that covers the concepts related to events, rules, roles and collaborating organizations for this application in ETKnet was developed. Terms used by different organizations can be located in the ontology by terminology searching. Services that implement knowledge rules and rule structures can be discovered through semantic matching using the concepts defined in the ontology. A tableau algorithm was extended to lazy-load only the needed instances and their relationships into main memory. With this extension, Lyra is capable of processing a large ontology database stored in secondary storage even when the ABox cannot be entirely loaded into memory.