Efficient Tree-Structured Categorical Retrieval - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2020

Efficient Tree-Structured Categorical Retrieval

Djamal Belazzougui
  • Fonction : Auteur
  • PersonId : 1085162

Résumé

We study a document retrieval problem in the new framework where D text documents are organized in a category tree with a pre-defined number h of categories. This situation occurs e.g. with taxomonic trees in biology or subject classification systems for scientific literature. Given a string pattern p and a category (level in the category tree), we wish to efficiently retrieve the t categorical units containing this pattern and belonging to the category. We propose several efficient solutions for this problem. One of them uses n(log σ(1 + o(1)) + log D + O(h)) + O(∆) bits of space and O(|p| + t) query time, where n is the total length of the documents, σ the size of the alphabet used in the documents and ∆ is the total number of nodes in the category tree. Another solution uses n(log σ(1 + o(1)) + O(log D)) + O(∆) + O(D log n) bits of space and O(|p| + t log D) query time. We finally propose other solutions which are more space-efficient at the expense of a slight increase in query time.
Fichier principal
Vignette du fichier
LIPIcs-CPM-2020-4.pdf (444.31 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-03049420 , version 1 (09-12-2020)

Identifiants

Citer

Djamal Belazzougui, Gregory Kucherov. Efficient Tree-Structured Categorical Retrieval. 31st Annual Symposium on Combinatorial Pattern Matching (CPM 2020), Jun 2020, Copenhagen, Denmark. ⟨10.4230/LIPIcs.CPM.2020.4⟩. ⟨hal-03049420⟩
47 Consultations
24 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More