A Fully Dynamic Algorithm for k-Regret Minimizing Sets

Yanhao Wang, Yuchen Li, Raymond Chi-Wing Wong, Kian-Lee Tan

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Selecting a small set of representatives from a large database is important in many applications such as multi-criteria decision making, web search, and recommendation. The k-regret minimizing set (k-RMS) problem was recently proposed for representative tuple discovery. Specifically, for a large database P of tuples with multiple numerical attributes, the k-RMS problem returns a size-r subset Q of P such that, for any possible ranking function, the score of the top-ranked tuple in Q is not much worse than the score of the k th-ranked tuple in P. Although the k-RMS problem has been extensively studied in the literature, existing methods are designed for the static setting and cannot maintain the result efficiently when the database is updated. To address this issue, we propose the first fully-dynamic algorithm for the k-RMS problem that can efficiently provide the up-to-date result w.r.t. any tuple insertion and deletion in the database with a provable guarantee. Experimental results on several real-world and synthetic datasets demonstrate that our algorithm runs up to four orders of magnitude faster than existing k-RMS algorithms while providing results of nearly equal quality.

Original languageEnglish
Title of host publication2021 IEEE 37th International Conference on Data Engineering (ICDE)
Number of pages12
PublisherIEEE
Publication date2021
Pages1631-1642
ISBN (Print)978-1-7281-9185-0
ISBN (Electronic)978-1-7281-9184-3
DOIs
Publication statusPublished - 2021
MoE publication typeA4 Article in conference proceedings
EventIEEE International Conference on Data Engineering - Chania, Greece
Duration: 19 Apr 202123 Apr 2021
Conference number: 37
https://icde2021.gr/

Publication series

NameIEEE International Conference on Data Engineering
PublisherIEEE COMPUTER SOC
ISSN (Print)1084-4627

Fields of Science

  • 113 Computer and information sciences
  • regret minimizing set
  • dynamic algorithm
  • set cover
  • top-k query
  • skyline
  • COVER

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