Plas’O’Soins: An Interactive ICT Platform to Support Care Planning and Coordination within Home-Based Care

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

Interest-based recommendations for business intelligence users

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,

Schema-independent Querying for Heterogeneous Collections in NoSQL Document Stores

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,

A New Information-Theoretical Distance Measure for Evaluating Community Detection Algorithms

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

A Survey on evaluation of summarization methods

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

Offline versus Online Representation Learning of Documents Using External Knowledge

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

Unsupervised Collective-based Framework for Dynamic Retraining of Supervised Real-Time Spam Tweets Detection Model

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

Defining an Optimal Configuration Set for Selective Search Strategy – A Risk-Sensitive Approach

A search engine generally applies a single search strategy to any user query. The search combines many component processes (e.g., indexing, query expansion, search-weighting model, document ranking) and their hyperparameters, whose values are optimized based on past queries and then applied to all future queries. Even an optimized system may perform poorly on some queries, however, whereas another system might

Class Distribution Influence and Evaluation in Deep Learning – Application to Cancer Detection on Histological Images

Cancer is a fatal disease considered the second leading cause of death. Any advances in diagnosis and detection of cancer are thus crucial to save lives. The analysis of histological images -also known as Whole Slide Images (WSIs)- is considered as the gold standard in cancer diagnosis and staging. The pathologists’ manual analysis of WSIs is still the primary diagnosis

Startech M1 MP2I

FabSpace’s Startech is a program designed to encourage the development of entrepreneurial skills among college students and young researchers. The 2021 edition confirmed the concept as well as the interest of the participants in the support offered by the Startech. This recent edition of the Startech program, organized in Toulouse from September to December 2021, has generated the same enthusiasm