Frédérique Laforest

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Abstract— The SECAS Project (Simple Environment for Context Aware Systems) deals with the adaptation of applications to the context (user preferences and environment, terminal, etc.). We aim to develop a platform which makes the services, data and the user interface of applications adaptable to different context situations. In this domain, researches have(More)
The SECAS Project (Simple Environment for Context Aware Systems) is interested in the adaptation of applications to the context (preferences and environment of the user, used terminal ...). We aim to develop a platform which makes the data, the services and the user interface of applications adaptable to the various context situations. In this domain,(More)
Recommender Systems require specific datasets to evaluate their approach. They do not require the same information: descriptions of users or items or users interactions may be necessary, which is not gathered in today datasets. In this paper, we provide a dataset containing reviews from users on items, trust values between users, items category, categories(More)
The advent of semantic data on the Web requires efficient reasoning systems to infer RDF and OWL data. The linked nature and the huge volume of data entail efficiency and scalability challenges when designing productive inference systems. This paper presents Inferray, an implementation of RDFS, ρDF, and RDFS-Plus inference with improved performance over(More)
The SEFAGI project takes place in domains where many different user interfaces are needed in the same application. Instead of manually developing all the required windows, we propose a platform that automatically generates the needed code from high level descriptions of these windows. Code generation is done for standard screens and for small screens on(More)
End-users information capture remains a sensitive challenge, especially when information is under the form of documents. The difficulty concerns information indexing so that information can be precisely queried. In the DRUID project, the end-user captures XML paragraph-centric documents (i.e. documents with tags delimiting narrative text paragraphs), and a(More)
Cloud computing architectures involve different actors that can be divided into four categories: infrastructure- and platform-as-a-service providers, PaaS clients, and end users. These actors establish contracts with each other, with the intention of optimizing their costs and offering quality service. Paying attention to end users' context and providing(More)
Querying non-conventional data is recognized as a major issue in new environments and applications such as those occurring in pervasive computing. A key issue is the ability to query data, streams and services in a declarative way. Our overall objective is to make the development of pervasive applications easier through database principles. In this paper,(More)