Techreport3022: Unterschied zwischen den Versionen
Awa (Diskussion | Beiträge) K |
Awa (Diskussion | Beiträge) K |
||
Zeile 27: | Zeile 27: | ||
only be accessed via URI source lookups. We show how existing work on top-k join processing can be adapted to the Linked Data setting. We elaborate on strategies for a better estimation of scores of unprocessed | only be accessed via URI source lookups. We show how existing work on top-k join processing can be adapted to the Linked Data setting. We elaborate on strategies for a better estimation of scores of unprocessed | ||
join result (to obtain tighter bounds for early termination) and for a more aggressive pruning of results. Based on experiments on real-world Linked Data, we show that the proposed top-k join processing technique substantially improves runtime performance. | join result (to obtain tighter bounds for early termination) and for a more aggressive pruning of results. Based on experiments on real-world Linked Data, we show that the proposed top-k join processing technique substantially improves runtime performance. | ||
+ | |Download=Ldtopk-tr-2011.pdf | ||
|Projekt=CollabCloud | |Projekt=CollabCloud | ||
|Forschungsgruppe=Wissensmanagement | |Forschungsgruppe=Wissensmanagement |
Version vom 19. Dezember 2011, 18:04 Uhr
Published: 2011
Dezember
Institution: Institut AIFB, KIT
Archivierungsnummer:3022
Kurzfassung
In recent years, top-k query processing has attracted much attention in large-scale scenarios, where computing only the k “best” results is often sufficient. Top-k query processing has been dealt with in different contexts. One line of research targets the so-called top-k join
problem, where the k best final results are obtained through joining partial results. In this paper, we study top-k join in a Linked Data setting, where partial results to be joined are located in different sources and can
only be accessed via URI source lookups. We show how existing work on top-k join processing can be adapted to the Linked Data setting. We elaborate on strategies for a better estimation of scores of unprocessed
join result (to obtain tighter bounds for early termination) and for a more aggressive pruning of results. Based on experiments on real-world Linked Data, we show that the proposed top-k join processing technique substantially improves runtime performance.
Download: Media:Ldtopk-tr-2011.pdf