Article thumbnail

Clustered Elias-Fano Indexes

By GIULIO ERMANNO Pibiri and Rossano Venturini

Abstract

State-of-the-art encoders for inverted indexes compress each posting list individually. Encoding clusters of posting lists offers the possibility of reducing the redundancy of the lists while maintaining a noticeable query processing speed. In this article, we propose a new index representation based on clustering the collection of posting lists and, for each created cluster, building an ad hoc reference list with respect to which all lists in the cluster are encoded with Elias-Fano. We describe a posting lists clustering algorithm tailored for our encoder and two methods for building the reference list for a cluster. Both approaches are heuristic and differ in the way postings are added to the reference list: according to their frequency in the cluster or according to the number of bits necessary for their representation. The extensive experimental analysis indicates that significant space reductions are indeed possible, beating the best state-of-the-art encoders

Publisher: 'Association for Computing Machinery (ACM)'
Year: 2017
DOI identifier: 10.1145/3052773
OAI identifier: oai:arpi.unipi.it:11568/851321
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://doi.acm.org/10.1145/305... (external link)
  • http://hdl.handle.net/11568/85... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.