Efficient compressed indexing for approximate top-k string retrieval.

Héctor Ricardo Ferrada Escobar, Gonzalo Navarro

Forskningsoutput: Kapitel i bok/rapport/konferenshandlingKonferensbidragVetenskapligPeer review

Sammanfattning

Given a collection of strings (called documents), the {\em top-k document retrieval} problem is that of, given a string pattern p, finding the k documents where p appears most often. This is a basic task in most information retrieval scenarios. The best current implementations require 20-30 bits per character (bpc) and k to 4k microseconds per query, or 12-24 bpc and 1-10 milliseconds per query. We introduce a Lempel-Ziv compressed data structure that occupies 5-10 bpc to answer queries in around k microseconds. The drawback is that the answer is approximate, but we show that its quality improves asymptotically with the size of the collection, being over 85% already for patterns of length 4-6 on rather small collections, and improving for larger ones.
Originalspråkengelska
Titel på värdpublikationUnknown host publication
Utgivningsdatum2014
StatusPublicerad - 2014
MoE-publikationstypA4 Artikel i en konferenspublikation
EvenemangSymposium on String Processing and Information Retrieval - Ouro Preto, Brasilien
Varaktighet: 1 jan. 1800 → …
Konferensnummer: 21

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