Matches in ScholarlyData for { ?s ?p ?o. }
- item-1 hasContent ervin-ramollari.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent dimitrios-kourtesis.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent dimitris-dranidis.
- item-3 next item-4.
- item-3 previous item-2.
- item-4 type ListItem.
- item-4 hasContent anthony-simons.
- item-4 previous item-3.
- 218 creator abraham-bernstein.
- 218 creator jonas-tappolet.
- 218 type InProceedings.
- 218 label "Applied Temporal RDF: Efficient Temporal Querying of RDF Data with SPARQL".
- 218 sameAs 218.
- 218 abstract "Many applications operate on time-“sensitive” data. Some of these data are only valid for certain intervals (e.g., job-assignments, versions of software code), others describe temporal events that happened at certain points in time (e.g., a person’s birthday). Until recently, the only way to incorporate time into Semantic Web models was as a data type property. Temporal RDF, however, considers time as an additional dimension in data preserving the semantics of time. In this paper we present a syntax and storage format based on named graphs to express temporal RDF. Given the restriction to preexisting RDF-syntax, our approach can perform any temporal query using standard SPARQL syntax only. For convenience, we introduce a shorthand format called T-SPARQL for temporal queries and show how T-SPARQL queries can be translated to standard SPARQL. Additionally, we show that, depending on the underlying data's nature, the temporal RDF approach vastly reduces the number of triples by eliminating redundancies resulting in an increased performance for processing and querying. Last but not least, we introduce a new indexing approach method that can significantly reduce the time needed to execute time point queries (e.g., what happened on January 1st).".
- 218 hasAuthorList authorList.
- 218 hasTopic Annotation.
- 218 hasTopic Data.
- 218 hasTopic Data_integration.
- 218 hasTopic Linked_Data.
- 218 hasTopic Optimization_(computer_science).
- 218 hasTopic Performance_engineering.
- 218 hasTopic Query.
- 218 hasTopic SPARQL.
- 218 hasTopic Scalability.
- 218 hasTopic Semantic_Web.
- 218 isPartOf proceedings.
- 218 keyword "temporal RDF".
- 218 keyword "temporal query language".
- 218 title "Applied Temporal RDF: Efficient Temporal Querying of RDF Data with SPARQL".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasLastItem item-2.
- item-1 type ListItem.
- item-1 hasContent jonas-tappolet.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent abraham-bernstein.
- item-2 previous item-1.
- 219 creator eva-kuehn.
- 219 creator martin-murth.
- 219 type InProceedings.
- 219 label "A Heuristics Framework for Semantic Subscription Processing".
- 219 sameAs 219.
- 219 abstract "The increasing adoption of semantic web technology in application scenarios with frequently changing data has imposed new requirements on the underlying tools. Reasoning algorithms need to be optimized for the processing of dynamic knowledge bases and semantic frameworks have to provide novel mechanisms for detecting changes of knowledge. Today, the latter is mostly realized by implementing simple polling mechanisms. However, this implies client-side post-processing of the received results, causes high response times and limits the overall throughput of the system. In this paper, we present a heuristics framework for realizing a subscription mechanism for dynamic knowledge bases. By analyzing similarities between published information and resulting notifications, heuristics can be employed to “guess” subsequent notifications. As testing the correctness of guessed notifications can be implemented efficiently, notifications can be delivered to the subscribers in an earlier processing phase and the system throughput can be increased. We experimentally evaluate our approach based on a concrete application scenario.".
- 219 hasAuthorList authorList.
- 219 hasTopic Collaborative_software.
- 219 hasTopic Database_management_system.
- 219 hasTopic Performance_engineering.
- 219 hasTopic Scalability.
- 219 hasTopic Semantic_Web.
- 219 isPartOf proceedings.
- 219 keyword "continuous queries".
- 219 keyword "heuristics framework".
- 219 keyword "incremental result set updates".
- 219 keyword "semantic subscription processing".
- 219 keyword "similarity heuristics".
- 219 title "A Heuristics Framework for Semantic Subscription Processing".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasLastItem item-2.
- item-1 type ListItem.
- item-1 hasContent martin-murth.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent eva-kuehn.
- item-2 previous item-1.
- 22 creator bernardo-cuenca-grau.
- 22 creator ernesto-jimenez-ruiz.
- 22 creator ian-horrocks.
- 22 creator rafael-berlanga.
- 22 type InProceedings.
- 22 label "Ontology Integration Using Mappings: Towards Getting the Right Logical Consequences".
- 22 sameAs 22.
- 22 abstract "We propose a general method and novel algorithmic techniques to facilitate the integration of independently developed ontologies using mappings. Our method and techniques aim at helping users understand and evaluate the semantic consequences of the integration, as well as to detect and fix potential errors. We also present a system that implements our approach, and a preliminary evaluation which suggests that our approach is both useful and feasible in practice.".
- 22 hasAuthorList authorList.
- 22 hasTopic Evaluation.
- 22 hasTopic Ontology_%28computer_science%29.
- 22 hasTopic Ontology_alignment.
- 22 hasTopic Ontology_engineering.
- 22 hasTopic Semantic_Web.
- 22 isPartOf proceedings.
- 22 keyword "OWL".
- 22 keyword "Ontology Integration".
- 22 keyword "Ontology Mapping".
- 22 keyword "Semantic Web".
- 22 title "Ontology Integration Using Mappings: Towards Getting the Right Logical Consequences".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.