Ranked Document Retrieval in (Almost) No Space
Abstract
Ranked document retrieval is a fundamental task in search engines. Such queries are solved with inverted indexes that require additional 45%-80% of the compressed text space, and take tens to hundreds of microseconds per query. In this paper we show how ranked document retrieval queries can be solved within tens of milliseconds using essentially no extra space over an in-memory compressed representation of the document collection. More precisely, we enhance wavelet trees on bytecodes (WTBCs), a data structure that rearranges the bytes of the compressed collection, so that they support ranked conjunctive and disjunctive queries, using just 6%-18% of the compressed text space.
Keywords
Cite
@article{arxiv.1207.5425,
title = {Ranked Document Retrieval in (Almost) No Space},
author = {Nieves R. Brisaboa and Ana Cerdeira-Pena and Gonzalo Navarro and Oscar Pedreira},
journal= {arXiv preprint arXiv:1207.5425},
year = {2015}
}
Comments
This is an extended version of the paper that will appear in Proc. of SPIRE'2012