Earth observation satellites have been capturing a variety of data about our planet for several decades, making many environmental applications possible such as change detection. Recently, deep learning methods have been proposed for urban change detection. However, there has been limited work done on the application of such methods to the annotation of unlabeled images in the case of change
BackgroundDue to the rising demand in home healthcare services in France as well as in other European countries, homecare organizations are facing challenges in terms of coordination and continuity of care. In both cases, the problem is linked to the efficiency in which care interventions are distributed and managed among the different participants involved in home care processes. Project Plas’O’Soins
It is quite common these days for experts, casual analysts, executives and data enthusiasts, to analyze large datasets through user-friendly interfaces on top of Business Intelligence (BI) systems. However, current BI systems do not adequately detect and characterize user interests, which may lead to tedious and unproductive interactions. In this paper, we propose a collaborative recommender system for BI interactions,
NoSQL document stores are well-tailored to efficiently load and manage massive collections of heterogeneous documents without any prior structural validation. However, this flexibility becomes a serious challenge when querying heterogeneous documents, and hence the user has to build complex queries or reformulate existing queries whenever new schemas are introduced in a collection. In this paper we propose a novel approach,
Community detection is a research area from network science dealing with the investigation of complex networks such as social or biological networks, aiming to identify sub groups (communities) of entities (nodes) that are more closely related to each other inside the community than with the remaining entities in the network. Various community detection algorithms have been developed and used in
The increasing volume of textual information on any topic requires its compression to allow humans to digest it. This implies detecting the most important information and condensing it. These challenges have led to new developments in the area of Natural Language Processing (NLP) and Information Retrieval (IR) such as narrative summarization and evaluation methodologies for narrative extraction. Despite some progress
An intensive recent research work investigated the combined use of hand-curated knowledge resources and corpus-driven resources to learn effective text representations. The overall learning process could be run by online revising the learning objective or by offline refining an original learned representation. The differentiated impact of each of the learning approaches on the quality of the learned representations has not
Twitter is one of the most popular social platforms. It has changed the way of communication and information dissemination through its real-time messaging mechanism. Recently, it has been used by researchers and industries as a new source of data for various intelligent systems, such as tweet sentiment analysis and recommendation systems, which require high data quality. However, due to its
Un moteur de recherche applique généralement une stratégie de recherche unique à toute requête d’un utilisateur. La recherche combine de nombreux processus (par exemple, l’indexation, l’expansion de la requête, le modèle de pondération de la recherche, le classement des documents) et leurs hyperparamètres, dont les valeurs sont optimisées sur la base des requêtes passées, puis appliquées à toutes les requêtes
Le cancer est une maladie mortelle considérée comme la deuxième cause de décès. Toute avancée dans le diagnostic et la détection de cancer est donc cruciale pour sauver des vies. L’analyse d’images histologiques – Whole Slide Images (WSI) – est considérée comme la référence dans le diagnostic et l’étude du stade du cancer. L’analyse manuelle de ces images par les