Paper Info
Title
Improving the performance of semantic web applications with SPARQL query caching
Abstract
The performance of triple stores is one of the major obstacles for the deployment of semantic technologies in many usage scenarios. In particular, Semantic Web applications, which use triple stores as persistence backends, trade performance for the advantage of flexibility with regard to information structuring. In order to get closer to the performance of relational database-backed Web applications, we developed an approach for improving the performance of triple stores by caching query results and even complete application objects. The selective invalidation of cache objects, following updates of the underlying knowledge bases, is based on analysing the graph patterns of cached SPARQL queries in order to obtain information about what kind of updates will change the query result. We evaluated our approach by extending the BSBM triple store benchmark with an update dimension as well as in typical Semantic Web application scenarios.
Year
DOI
Venue
2010
10.1007/978-3-642-13489-0_21
ESWC (2)
Keywords
Field
DocType
sparql query caching,triple store,trade performance,query result,information structure,typical semantic web application,cached sparql query,relational database-backed web application,semantic web application,complete application object,bsbm triple store benchmark,semantic technologies,relational database,knowledge base,semantic web
Web search query,Semantic technology,Information retrieval,Semantic Web Stack,Computer science,Semantic Web,SPARQL,Semantic analytics,Social Semantic Web,Database,Semantic computing
Conference
Volume
ISSN
ISBN
6089
0302-9743
3-642-13488-2
Citations 
PageRank 
References 
42
1.76
11
Authors
3
Name
Order
Citations
PageRank
Michael Martin11358.40
Jörg Unbehauen2686.85
Sören Auer35711418.56