Titel: Fast Distributed Top-q and Top-k Query Processing

Top-k queries retrieve the k results of a query which score best for an objective function representing the preferences of users. To require that the returned results also have to satisfy the preferences to a certain degree we introduce top-q queries which return all results which approximate the user preferences to at least some minim degree q. We show how top-q queries and top-k queries can be combined enabling the user to post a large number of interesting queries. Furthermore, we show that the calculation of top-q queries can be integrated in algorithms efficiently processing top-k queries. We implemented our approach and evaluated it against the fastest threshold based top-k query answering approaches (BPA-2). Our experiments showed an improvement by one to two orders of magnitude regarding time and memory requirements. Furthermore, we show how such queries can be processed in highly distributed peer-to-peer databases in an efficient way and propose an adaptive algorithm which takes several parameters of the network of databases into account to optimize the processing of distributed top-k queries.

Schlagworte: Top-q query answering, Top-k query answering, Approximate querying, Result ranking, Distributed Top-k queries, Adaptive query processing, p2p databases
Publikationstyp: Beitrag in Zeitschrift (Autorenschaft)
Art der Veröffentlichung Printversion
Erschienen in: Transactions on Large-Scale Data- and Knowledge-Centered Systems XLI
Transactions on Large-Scale Data- and Knowledge-Centered Systems XLI
zur Publikation
 ( Springer; A. Hameurlain, R. Wagner, T. Dang )
Erscheinungsdatum: 07.02.2019
Titel der Serie: LNCS
Bandnummer: 11390
Heftnummer: -
Erstveröffentlichung: Ja
Seite: S. 1 - 31


  • 978-3-662-58807-9
  • 978-3-662-58808-6
AC-Nummer: -
Open Access
  • Online verfügbar (nicht Open Access)


Organisation Adresse
Fakultät für Technische Wissenschaften
Institut für Informatik-Systeme
Universitätsstr. 65-67
A-9020  Klagenfurt
zur Organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt


  • 102 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
  • n.a.
Informationen zum Zitationsindex: Master Journal List
Peer Reviewed
  • Ja
  • Science to Science (Qualitätsindikator: III)
Klassifikationsraster der zugeordneten Organisationseinheiten:
  • Information and Communication Systems


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