Analysis of Caching and Replication Strategies for Web Applications
IEEE Internet Computing
Cache tables: paving the way for an adaptive database cache
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Scalable semantic web data management using vertical partitioning
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Column-store support for RDF data management: not all swans are white
Proceedings of the VLDB Endowment
SP^2Bench: A SPARQL Performance Benchmark
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Semantics and complexity of SPARQL
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Caching intermediate result of SPARQL queries
Proceedings of the 20th international conference companion on World wide web
Creating knowledge out of interlinked data: making the web a data washing machine
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Enabling fine-grained HTTP caching of SPARQL query results
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
To cache or not to cache: the effects of warming cache in complex SPARQL queries
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part II
An empirical survey of Linked Data conformance
Web Semantics: Science, Services and Agents on the World Wide Web
Semantic caching for semantic web applications
JIST'11 Proceedings of the 2011 joint international conference on The Semantic Web
Freshening up while staying fast: towards hybrid SPARQL queries
EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
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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.