Adaptive searching in succinctly encoded binary relations and tree-structured documents

  • Authors:
  • Jérémy Barbay;Alexander Golynski;J. Ian Munro;S. Srinivasa Rao

  • Affiliations:
  • David R. Cheriton School of Computer Science, University of Waterloo, Canada;David R. Cheriton School of Computer Science, University of Waterloo, Canada;David R. Cheriton School of Computer Science, University of Waterloo, Canada;Computational Logic and Algorithms group, IT University of Copenhagen, Denmark

  • Venue:
  • CPM'06 Proceedings of the 17th Annual conference on Combinatorial Pattern Matching
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

The most heavily used methods to answer conjunctive queries on binary relations (such as the one associating keywords with web pages) are based on inverted lists stored in sorted arrays and use variants of binary search. We show that a succinct representation of the binary relation permits much better results, while using space within a lower order term of the optimal. We apply our results not only to conjunctive queries on binary relations, but also to queries on semi-structured documents such as XML documents or file-system indexes, using a variant of an adaptive algorithm used to solve conjunctive queries on binary relations.