From Human and Social Indexing to Automatic Indexing in the Era of Big Data and Open Data

Autor: Khemiri, Nabil, Sidhom, Sahbi
Přispěvatelé: Université de Jendouba (UJ), Building artificial Intelligence between trust, Responsibility and Decision (BIRD), Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), ISTE UK & WILEY, Imad Saleh
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Systems and Uses of Digital Sciences for Knowledge Organization
ISTE UK & WILEY. Systems and Uses of Digital Sciences for Knowledge Organization, 9 (1), ISTE UK & WILEY, 153-164 pp., 2022, Volume 9-Digital Tools and Uses SET by Imad Saleh, ISBN : 9781786307736
Popis: International audience; In the era of Big Data and Open Data, a massive and heterogeneous collections of documents (from text to multimedia) are created, managed and stored electronically. to make these documents more usable, a manual and/or automatic indexing process allows to create a representation of documents by a set of metadata, descriptors and social tags. These representations then make it easier to find information in a massive and scalable collection of documents from different sources (social networks, open data, …) to respond to user information needs (user requests). Numerous research studies have been carried out to propose indexing approaches depending on the type of indexed documents. Also, the evolution of indexing Methods, documents representation, electronic content, Big Data and Open Data. This paper presents a state of the art of approaches and methodologies ranging from manual and automatic indexing to algorithmic methods in the era of Big Data and Open Data.
Databáze: OpenAIRE