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Information Retrieval, Document and Semantic Web

Recherche d’information, document et web sémantique

RIDoWS - ISSN 2516-3280 - © ISTE Ltd

Aims and scope

Objectifs de la revue

The diversity in forms of documents (multimedia, multilingual, with or without a structure) and in their uses encourages different communities to mingle more and more.


Information Retrieval, Document and Semantic Web is a meeting point for these scientific or industrial communities who are interested in information research, the semantic web, the analysis of documents (texts, images, sounds, videos, etc.) or in the collection of documents.

La multiplicité des formes de documents (multimédia, multilingue, structuré ou non) et des usages favorise de plus en plus un brassage entre différentes communautés.

Recherche d’information, document et web sémantique est un point de rencontre pour ces communautés scientifiques ou industrielles qui s’intéressent à la recherche d’information, au web sémantique, à l’analyse de documents (textes, images, sons, vidéos...) ou à la collection de documents.

Journal issues


Volume 17- 1

Issue 1


Volume 18- 2

Issue 1


Volume 19- 3

Issue 1

Recent articles

Detection of weak signals in weakly structured data masses

This paper is related to a project aiming at discovering weak signals from different streams of information, possibly sent by whistleblowers in a platform as GlobalLeaks. The study presented in this paper tackles the (...)

DataNews: contextualisation of quantified values in wires

The Open Data allows the access to plentiful data, with a large coverage, but none of them offers a structured databased around news. Through DataNews, our goal is to seek for data automatically so as to provide means to (...)

Influence over Networks, a modelling proposal

This paper focuses on influencers, defined as individuals succeeding to have an impact on the decision process of other individuals simply through interaction. The success of social networks in the last decade led to an (...)

Data correction for transcription in crowdsourcing. A feedback from RECITAL platform.

Crowdsourcing have been widely deployed to cover some challenges in digital humanities, like in the transcription of old handwritten documents. Such approach is especially useful to tackle existing limits in automatic (...)

Earth Observation Datasets for Change Detection in Forests

The automatic detection of changes in forests (deforestation, reforestation) relies on various data sets. This article reviews data sets both global and local that can be used to evaluate tasks of land cover classification, (...)

Construction(s) and contradictions of research data in the Humanities and Social Sciences

In the last decade, political injunctions to curate and share research data have increased significantly. A survey conducted in 2017 in Rennes 2, a french Humanities and Social Sciences university, enabled us to question (...)

Automatic analysis of old documents: taking advantage of an incomplete, heterogeneous and noisy corpus

In this article we try to tackle some problems arising with noisy and heterogeneous data in the domain of digital humanities. We investigate a corpus known as the mazarinades corpus which gathers around 5,500 documents in (...)

Harness the hetorogeneity in textual data

Over the last decades, there has been an increasing use of information systems, resulting in an exponential increase in textual data. Although the volumetric dimension of these textual data has been resolved, its (...)

Editorial Board

Editor in Chief




Laboratoire I3S
Université Nice Sophia Antipolis

IRIT – Université Paul Sabatier

LIPN – Université Paris 13

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