A relational vector space model using an ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
A relational vector space model using an advanced weighting scheme for image retrieval
Auteur(s) :
Martinet, Jean [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
FOX MIIRE [LIFL]
Chiaramella, Yves [Auteur]
Laboratoire d'Informatique de Grenoble [LIG]
Mulhem, Philippe [Auteur correspondant]
Modélisation et Recherche d’Information Multimédia [Grenoble] [MRIM]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
FOX MIIRE [LIFL]
Chiaramella, Yves [Auteur]
Laboratoire d'Informatique de Grenoble [LIG]
Mulhem, Philippe [Auteur correspondant]
Modélisation et Recherche d’Information Multimédia [Grenoble] [MRIM]
Titre de la revue :
Information Processing and Management
Pagination :
391-414
Éditeur :
Elsevier
Date de publication :
2011-05
ISSN :
0306-4573
Mot(s)-clé(s) en anglais :
Information retrieval
Vector space model
Conceptual graph
Image indexing
Weighting scheme
Evaluation
Vector space model
Conceptual graph
Image indexing
Weighting scheme
Evaluation
Discipline(s) HAL :
Informatique [cs]/Autre [cs.OH]
Informatique [cs]/Recherche d'information [cs.IR]
Informatique [cs]/Recherche d'information [cs.IR]
Résumé en anglais : [en]
In this paper, we lay out a relational approach for indexing and retrieving photographs from a collection. The increase of digital image acquisition devices, combined with the growth of the World Wide Web, requires the ...
Lire la suite >In this paper, we lay out a relational approach for indexing and retrieving photographs from a collection. The increase of digital image acquisition devices, combined with the growth of the World Wide Web, requires the development of information retrieval (IR) models and systems that provide fast access to images searched by users in databases. The aim of our work is to develop an IR model suited to images, integrating rich semantics for representing this visual data and user queries, which can also be applied to large corpora. Our proposal merges the vector space model of IR - widely tested in textual IR - with the conceptual graph (CG) formalism, based on the use of star graphs (i.e. elementary CGs made up of a single relation connected to some concepts representing image objects). A novel weighting scheme for star graphs, based on image objects size, position, and image heterogeneity is outlined. We show that integrating relations into the vector space model through star graphs increases the system's precision, and that the results are comparable to those from graph projection systems, and also that they shorten processing time for user queries.Lire moins >
Lire la suite >In this paper, we lay out a relational approach for indexing and retrieving photographs from a collection. The increase of digital image acquisition devices, combined with the growth of the World Wide Web, requires the development of information retrieval (IR) models and systems that provide fast access to images searched by users in databases. The aim of our work is to develop an IR model suited to images, integrating rich semantics for representing this visual data and user queries, which can also be applied to large corpora. Our proposal merges the vector space model of IR - widely tested in textual IR - with the conceptual graph (CG) formalism, based on the use of star graphs (i.e. elementary CGs made up of a single relation connected to some concepts representing image objects). A novel weighting scheme for star graphs, based on image objects size, position, and image heterogeneity is outlined. We show that integrating relations into the vector space model through star graphs increases the system's precision, and that the results are comparable to those from graph projection systems, and also that they shorten processing time for user queries.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
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