A web 2.0 archive to access, annotate and retrieve manuscripts

Autor: Reim Doumat, Jean-Marie Pinon, Elöd Egyed-Zsigmond
Přispěvatelé: Distribution, Recherche d'Information et Mobilité (DRIM), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2)
Rok vydání: 2011
Předmět:
Zdroj: Multimedia Tools and Applications
Multimedia Tools and Applications, Springer Verlag, 2011, pp.1-21. ⟨10.1007/s11042-011-0851-9⟩
ISSN: 1573-7721
1380-7501
DOI: 10.1007/s11042-011-0851-9
Popis: International audience; The Web development encouraged different organizations and individuals to expose their multimedia documents on the internet. Additionally, the migration to web 2.0 offered users the chance to comment and annotate the contents of these multimedia documents. Museums and libraries are particularly interested in users’ feedback and work, because many collections, such as handwritten manuscripts, are still puzzles for archivists. Therefore any feedback concerning these contents will be welcomed. This article focuses on the design and the implementation of a web archive. The main objective is enabling users to annotate easily and remotely manuscript documents using web 2.0 application. User annotations are considered important to enrich the archive contents with essential information nevertheless not all users are experts in the manuscript domain. Accordingly, users need a kind of assistance during the search and annotation processes. The proposed assistant in our archive is a recommender system; it relies on registered traces of the user interaction with the documents to generate suggestions.
Databáze: OpenAIRE