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Markus Krötzsch (Diskussion | Beiträge) K (Textersetzung - „}} {{Publikation Author |Rank=3 |Author=“ durch „; “) |
Sebastian Rudolph (Diskussion | Beiträge) Keine Bearbeitungszusammenfassung |
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{{Publikation Erster Autor | {{Publikation Erster Autor | ||
|ErsterAutorVorname=Thanh | |||
|ErsterAutorNachname=Tran | |ErsterAutorNachname=Tran | ||
|FurtherAuthors=Günter Ladwig; Sebastian Rudolph | |||
|FurtherAuthors=Günter Ladwig | |||
; Sebastian Rudolph | |||
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|To appear=0 | |To appear=0 | ||
|Year=2013 | |Year=2013 | ||
|Journal=IEEE | |Journal=IEEE Transactions on Knowledge and Data Engineering | ||
|Volume=25 | |Volume=25 | ||
|Number=9 | |Number=9 | ||
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|Bild=TKDE.jpg | |Bild=TKDE.jpg | ||
|Abstract=We propose the use of a structure index for RDF. It can be used for querying RDF data for which the schema is incomplete or not available. More importantly, we leverage it for a structure-oriented approach to RDF data partitioning and query processing. Based on information captured by the structure index, similarly structured data elements are physically grouped and stored contiguously on disk. At querying time, the index is used for "structure-level" processing to identify the groups of data that match the query structure. Structure-level processing is then combined with standard "data-level" operations that involve retrieval and join procedures executed against the data. In the experiment, our solution provides several times faster performance than a state-of-the-art technique for data partitioning and query processing, and compares favorably with full-fledged RDF stores. | |Abstract=We propose the use of a structure index for RDF. It can be used for querying RDF data for which the schema is incomplete or not available. More importantly, we leverage it for a structure-oriented approach to RDF data partitioning and query processing. Based on information captured by the structure index, similarly structured data elements are physically grouped and stored contiguously on disk. At querying time, the index is used for "structure-level" processing to identify the groups of data that match the query structure. Structure-level processing is then combined with standard "data-level" operations that involve retrieval and join procedures executed against the data. In the experiment, our solution provides several times faster performance than a state-of-the-art technique for data partitioning and query processing, and compares favorably with full-fledged RDF stores. | ||
|Download=Strucidx-tkde.pdf | |||
|Link=http://www.computer.org/csdl/trans/tk/2013/09/ttk2013092076-abs.html | |Link=http://www.computer.org/csdl/trans/tk/2013/09/ttk2013092076-abs.html | ||
|DOI Name=10.1109/TKDE.2012.134 | |DOI Name=10.1109/TKDE.2012.134 | ||
|Forschungsgruppe=Computational Logic | |Forschungsgruppe=Computational Logic | ||
|DOI=http://doi.ieeecomputersociety.org/10.1109/TKDE.2012.134 | |DOI=http://doi.ieeecomputersociety.org/10.1109/TKDE.2012.134 | ||
}} | |||
{{Forschungsgebiet Auswahl | |||
|Forschungsgebiet=Semantische Technologien | |||
}} | }} | ||
Aktuelle Version vom 14. November 2014, 22:49 Uhr
Managing Structured and Semistructured RDF Data Using Structure Indexes
Thanh TranThanh Tran, Günter LadwigGünter Ladwig, Sebastian RudolphSebastian Rudolph
Thanh Tran, Günter Ladwig, Sebastian Rudolph
Managing Structured and Semistructured RDF Data Using Structure Indexes
IEEE Transactions on Knowledge and Data Engineering, 25(9):2076-2089, 2013
Managing Structured and Semistructured RDF Data Using Structure Indexes
IEEE Transactions on Knowledge and Data Engineering, 25(9):2076-2089, 2013
- KurzfassungAbstract
We propose the use of a structure index for RDF. It can be used for querying RDF data for which the schema is incomplete or not available. More importantly, we leverage it for a structure-oriented approach to RDF data partitioning and query processing. Based on information captured by the structure index, similarly structured data elements are physically grouped and stored contiguously on disk. At querying time, the index is used for "structure-level" processing to identify the groups of data that match the query structure. Structure-level processing is then combined with standard "data-level" operations that involve retrieval and join procedures executed against the data. In the experiment, our solution provides several times faster performance than a state-of-the-art technique for data partitioning and query processing, and compares favorably with full-fledged RDF stores. - Weitere Informationen unter:Further Information: Link
- Forschungsgruppe:Research Group: Computational LogicComputational Logic
@article{TLR2013,
author = {Thanh Tran and G{\"{u}}nter Ladwig and Sebastian Rudolph},
title = {Managing Structured and Semistructured {RDF} Data Using Structure
Indexes},
journal = {IEEE Transactions on Knowledge and Data Engineering},
volume = {25},
number = {9},
publisher = {IEEE},
year = {2013},
pages = {2076-2089},
doi = {10.1109/TKDE.2012.134}
}
