CERIST Digital Library est le dépôt institutionnel du Centre de Recherche sur l'Information Scientifique et Technique qui donne accès à toute la production du CERIST: articles de conférence, rapports techniques ou de recherche, thèses, supports de cours, etc. .

Dans CERIST DL, vous pouvez :

Parcourir la production scientifique du CERIST par communautés, collections, auteurs, etc.

Rechercher par : Titre, Auteur, Mots clés, Date de publication, Date de soumission, etc.

Consulter les différents articles et produits. Il est à noter que certains articles sont soumis à une restriction d'accès.

Recevoir des alertes sur les nouveaux articles et items et cela, en vous abonnant à une ou plusieurs collections.

Select a community to browse its collections.

  • Leveraging Learners' Activity Logs for Course Reading Analytics Using Session-Based Indicators 

    Sadallah, Madjid; Encelle, Benoît; Maredj, Azze-Eddine; Prié, Yannick
    In : (Inderscience, 2018)
    A challenge that course authors face when reviewing their contents is to detect how to improve their courses in order to meet the expectations of their learners. In this paper, we propose an analytical approach that exploits learners' logs of reading to provide authors with insightful data about the consumption of their ...
  • Visual Data Mining by Virtual Reality for Protein-Protein Interaction Networks 

    Aouaa Noureddine;; Gherbi Rachid; Meziane Abdelkrim; Hayat Hadjar; Insaf Setitra
    In : Rapports de recherche internes, (CERIST, Alger, 2018-03-28)
    Currently, visualization techniques in the genetic field require a very important modeling phase in terms of resources. Traditional modeling techniques (in two dimensions) are rarely adapted to manage and process this mass of information. To overcome this kind of problem, we propose to use a new graph modeling technique ...
  • Random input helps searching predecessors 

    Belazzougui, Djamal; Kaporis, Alexis C.; Spirakis, Paul G.
    In : (CEUR-WS.org, Athènes, 2018-06-17)
    A data structure problem consists of the finite sets: D of data, Q of queries, A of query answers, associated with a function f : D ×Q → A. The data structure of file X is “static” (“dynamic”) if we “do not” (“do”) require quick updates as X changes. An important goal is to compactly encode a file X ∈ D, such that ...
  • Angle Minimization and Graph Analysis for text line segmentation in handwritten documents 

    Setitra, Insaf; Meziane, Abdelkrim
    In : Rapports de recherche internes, (CERIST, Alger, 2018-07-08)
    We propose in this paper a novel approach for text line segmentation in handwritten documents. The approach is based on angle minimization and graph analysis for text lines extraction. We apply our approach on images of ICDAR 2013 Handwriting Segmentation Contest, and give details about its robustness against skew ...
  • Fast matching statistics in small space 

    Belazzougui, Djamal; Cunial, Fabio; Denas, Olgert
    In : (Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, L'Aquila, 2018-06-27)
    Computing the matching statistics of a string S with respect to a string T on an alphabet of size sigma is a fundamental primitive for a number of large-scale string analysis applications, including the comparison of entire genomes, for which space is a pressing issue. This paper takes from theory to practice an existing ...

View more

Tous les documents dans CERIST DIGITAL LIBRARY sont protégés par copyright, avec tous droits réservés. copyright © 2013-2015  CERIST
Powered by 
@mire NV