Wearable GPS device as a data collection method for travel research

Global Positioning System (GPS) devices are emerging as a potential means to collect improved data on the spatial aspects of personal travel. This paper builds on earlier work by Stopher and others on the use of passive GPS devices, for which additional non-GPS data may be added through a subsequent prompted recall survey. This paper presents sets of rules which can be applied to the raw data acquired by wearable GPS devices to determine the modes of travel used and the trip ends. Experiments have been performed in which the devices were tested for a range of different situations, including collecting data on trains, buses, and ferries, collecting data in urban canyons and also with respect to the cold start phenomenon. The paper also describes the procedures undertaken to download and analyse the data

Automatic Detection and Classification of Argument Components using Multi-task Deep Neural Network

International audienceIn this article we propose a novel method for automatically extracting and classifying argument components from raw texts. We introduce a multi-task deep learning framework exploiting weight parameters trained on auxiliary simple tasks, such as Part-Of-Speech tagging or chunking, in order to solve more complex tasks that require a fine-grained understanding of natural language. Interestingly, our results show that the use of advanced deep learning techniques framed in a multi-task setting enables competing with state-of-the-art systems that depend on handcrafted features

Digital Literacies as Socially Situated Pedagogical Processes: Genealogically Understanding Media, Information, and Digital Literacies

Despite the increasing importance of digital literacies for citizens to be able to participate in society, there is little scholarly agreement over what digital literacies entail. This conceptual ambiguity hinders the translation of digital literacies into educational programs and policies that foster citizens' digital literacies and inclusion. While various authors have attempted to define digital literacy separately and in relation to other concepts, such as information literacy and media literacy, little attention has been paid to the historical backdrop of these concepts. By tracing the historical development of three literacies (media-, information-, and digital literacy), we reflect on how societal demands shaped conceptual frameworks of these literacies and how these conceptualizations are situated within the broader pedagogical systems that aim to enable participation in digital societies. Using a genealogical approach, we explore and describe the changes in definition, understanding, and enactment of the three literacies, which illustrate how these concepts have developed towards the conceptual frameworks we employ today. Based on this analysis, we argue that digital literacies must be flexible to anticipate challenges that result from the rise of new technologies and need to be appropriated within different socio-cultural contexts. We pledge for an understanding of digital literacies as socially situated pedagogical processes aimed at the way citizens appropriate digital practices within their daily lives. This implies shifting away from formulating one-size-fits-all understandings based upon generic uses of digital technologies. Instead, we must appropriate the understandings of digital literacies based upon their socio-technical, cultural, political, economic, and material dimensions

Editorial: Digital In- and Exclusion in Everyday Life: Practices and Literacies Across the Lifespan

In this thematic issue of Media and Communication titled Practices of Digital In- and Exclusion in Everyday Life, we bring together insights from around the world to offer a diverse set of perspectives on digital practices and digital literacies across the lifespan. Moreover, emphasizing the development of digital literacies as a situated social practice, this thematic issue provides insights into the social contexts through which people develop digital literacy practices, how they construct and integrate social norms around technologies, and the links between digital literacies and (digital) citizenship. As concerns about digital in- and exclusion grow, this thematic issue hosts numerous relevant studies by academics that collectively help us gain insight into the impact of digital in- and exclusion in everyday life across the lifespan, gaining insight into the role of different contextual factors, including time, place, and social, economic, and political contexts in the ways in which citizens use digital media and develop digital literacies

Analyse automatique d’arguments et apprentissage multi-tâches : un cas d’étude

National audienceNous proposons une étude sur l’analyse automatique d’arguments via des techniques d’apprentissage supervisé exploitant le paradigme de l’apprentissage multi-tâches. Nous définissons pour cela une approche multi-tâches à base d’apprentissage profond que nous évaluons sur un cas d’étude spécifique portant sur l’extraction d’arguments dans un corpus de dissertations. Les résultats obtenus permettent de discuter l’intérêt de définir un modèle multi-tâches unique – optimisé sur différents critères en tirant parti de la diversité des tâches d’apprentissage auxquelles il est confronté – par rapport à un ensemble de classifieurs entraînés de manière indépendante et spécifique. Nous montrons en particulier l’impact de l’ajout de tâches auxiliaires de bas niveau, telles que l’étiquetage morpho-syntaxique et l’analyse de dépendances grammaticales, pour l’obtention de classifieurs multi-tâches performants. Nous observons aussi que l’apprentissage multi-tâches permet l’obtention de modèles efficaces de performances semblables à l’état de l’art pour le cas d’étude traité

DÉfi Fouille de Textes 2019: indexation par extraction et appariement textuel

International audienceThis paper presents the contribution of the LGI2P (Laboratoire de Génie Informatique et d'Ingénierie de Production) team from IMT Mines Alès to the DEFT 2019 challenge (DÉfi Fouille de Textes). We detail two approches we devised for the tasks pertaining to (1) the indexing and to (2) the similarity of documents. Said approaches rely on proven and robust techniques from Information Retrieval and Natural Language Processing that have been adapted to the specificities of the corpus (biomedical text) and of the formulation of the tasks. For task 1, we propose an indexing-by-extraction approach applied on the corpus after a normalisation procedure (MAP=0.48) that we will detail further. For task 2, we proposed a similarity-based approach computed on vector representation of the documents (score=0.910) and study the impact of the choice of the similarity metric and of the document representation method on task performance.Cet article présente la contribution de l'équipe du Laboratoire de Génie Informatique et d'Ingénierie de Production (LGI2P) d'IMT Mines Alès au DÉfi Fouille de Textes (DEFT) 2019. Il détaille en particulier deux approches proposées pour les tâches liées à (1) l'indexation et à (2) la similarité de documents. Ces méthodes reposent sur des techniques robustes et éprouvées du domaine de la Recherche d'Information et du Traitement Automatique du Langage Naturel, qui ont été adaptées à la nature spécifique du corpus (biomédical/clinique) et couplées à des mécanismes développés pour répondre aux spécificités des tâches traitées. Pour la tâche 1, nous proposons une méthode d'indexation par extraction appliquée sur une version normalisée du corpus (MAP de 0,48 à l'évaluation) ; les spécificités de la phase de normalisation seront en particulier détaillées. Pour la tâche 2, au-delà de la présentation de l'approche proposée basée sur l'évaluation de similarités sur des représentations de documents (score de 0,91 à l'évaluation), nous proposons une étude comparative de l'impact des choix de la distance et de la manière de représenter les textes sur la performance de l'approche