Branch-and-bound algorithm for reverse top-k queries

  • Authors:

  • Akrivi Vlachou;Christos Doulkeridis;Kjetil Nørvåg;Yannis Kotidis

  • Affiliations:

  • Norwegian University of Science and Technology (NTNU), Trondheim, Norway;University of Piraeus, Piraeus, Greece;Norwegian University of Science and Technology (NTNU), Trondheim, Norway;Athens University of Economics and Business (AUEB), Athens, Greece

  • Venue:
  • Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Top-k queries return to the user only the k best objects based on the individual user preferences and comprise an essential tool for rank-aware query processing. Assuming a stored data set of user preferences, reverse top-k queries have been introduced for retrieving the users that deem a given database object as one of their top-k results. Reverse top-k queries have already attracted significant interest in research, due to numerous real-life applications such as market analysis and product placement. Currently, the most efficient algorithm for computing the reverse top-k set is RTA. RTA has two main drawbacks when processing a reverse top-k query: (i) it needs to access all stored user preferences, and (ii) it cannot avoid executing a top-k query for each user preference that belongs to the result set. To address these limitations, in this paper, we identify useful properties for processing reverse top-k queries without accessing each user's individual preferences nor executing the top-k query. We propose an intuitive branch-and-bound algorithm for processing reverse top-k queries efficiently and discuss novel optimizations to boost its performance. Our experimental evaluation demonstrates the efficiency of the proposed algorithm that outperforms RTA by a large margin.